DataFramed

The structured data that powers business decisions is more complex than the sequences processed by traditional AI models. Enterprise databases with their interconnected tables of customers, products, and transactions form intricate graphs that contain valuable predictive signals. But how can we effectively extract insights from these complex relationships without extensive manual feature engineering?Graph transformers are revolutionizing this space by treating databases as networks and learning directly from raw data. What if you could build models in hours instead of months while achieving better accuracy? How might this technology change the role of data scientists, allowing them to focus on business impact rather than data preparation? Could this be the missing piece that brings the AI revolution to predictive modeling?Jure Leskovec is a Professor of Computer Science at Stanford University, where he is affiliated with the Stanford AI Lab, the Machine Learning Group, and the Center for Research on Foundation Models.Previously, he served as Chief Scientist at Pinterest and held a research role at the Chan Zuckerberg Biohub. He is also a co-founder of Kumo.AI, a machine learning startup. Leskovec has contributed significantly to the development of Graph Neural Networks and co-authored PyG, a widely-used library in the field. Research from his lab has supported public health efforts during the COVID-19 pandemic and informed product development at companies including Facebook, Pinterest, Uber, YouTube, and Amazon.His work has received several recognitions, including the Microsoft Research Faculty Fellowship (2011), the Okawa Research Award (2012), the Alfred P. Sloan Fellowship (2012), the Lagrange Prize (2015), and the ICDM Research Contributions Award (2019). His research spans social networks, machine learning, data mining, and computational biomedicine, with a focus on drug discovery. He has received 12 best paper awards and five 10-year Test of Time awards at leading academic conferences.In the episode, Richie and Jure explore the need for a foundation model for enterprise data, the limitations of current AI models in predictive tasks, the potential of graph transformers for business data, and the transformative impact of relational foundation models on machine learning workflows, and much more.Links Mentioned in the Show:Jure’s PublicationsKumo AIConnect with JureCourse - Transformer Models with PyTorchRelated Episode: High Performance Generative AI Applications with Ram Sriharsha, CTO at PineconeRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Healthcare AI is rapidly evolving beyond simple diagnostic tools to comprehensive systems that can analyze and predict patient outcomes. With the rise of multimodal AI models that can process everything from medical images to patient records and genetic information, we're entering an era where AI could fundamentally transform how healthcare decisions are made. But how do we ensure these systems maintain patient privacy while still leveraging vast amounts of medical data? What are the technical challenges in building AI that can reason across different types of medical information? And how do we balance the promise of AI-assisted healthcare with the critical role of human medical professionals?Professor Aldo Faisal is Chair in AI & Neuroscience at Imperial College London, with joint appointments in Bioengineering and Computing, and also holds the Chair in Digital Health at the University of Bayreuth. He is the Founding Director of the UKRI Centre for Doctoral Training in AI for Healthcare and leads the Brain & Behaviour Lab and Behaviour Analytics Lab at Imperial’s Data Science Institute. His research integrates machine learning, neuroscience, and human behaviour to develop AI technologies for healthcare. He is among the few engineers globally leading their own clinical trials, with work focused on digital biomarkers and AI-based medical interventions. Aldo serves as Associate Editor for Nature Scientific Data and PLOS Computational Biology, and has chaired major conferences like KDD, NIPS, and IEEE BSN. His work has earned multiple awards, including the $50,000 Toyota Mobility Foundation Prize, and is regularly featured in global media outlets.In the episode, Richie and Aldo explore the advancements in AI for healthcare, including AI's role in diagnostics and operational improvements, the ambitious Nightingale AI project, challenges in handling diverse medical data, privacy concerns, and the future of AI-assisted medical decision-making, and much more.Links Mentioned in the Show:Aldo’s PublicationsConnect with AldoProject: What is Your Heart Rate Telling You?Related Episode: Using Data to Optimize Costs in Healthcare with Travis Dalton and Jocelyn Jiang President/CEO & VP of Data & Decision Science at MultiPlanRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The relationship between humans and AI in the workplace is rapidly evolving beyond simple automation. As companies deploy thousands of AI agents to handle everything from expense approvals to customer success management, a new paradigm is emerging—one where humans become orchestrators rather than operators. But how do you determine which processes should be handled by AI and which require human judgment? What governance structures need to be in place before deploying AI at scale? With the potential to automate up to 80% of business processes, organizations must carefully consider not just the technology, but the human element of AI-driven transformation.Steve Lucas is the Chairman and CEO of Boomi, marking his third tenure as CEO. With nearly 30 years of enterprise software leadership, he has held senior roles at leading cloud organizations including Marketo, iCIMS, Adobe, SAP, Salesforce, and BusinessObjects. He led Marketo through its multi-billion-dollar acquisition by Adobe and drove strategic growth at iCIMS, delivering significant investments and transformation. A proven leader in scaling software companies, Steve is also the author of the national bestseller Digital Impact and holds a business degree from the University of Colorado.In the episode, Richie and Steve explore the importance of choosing the right tech stack for your business, the challenges of managing complex systems, the role of AI in transforming business processes, and the need for effective AI governance. They also discuss the future of AI-driven enterprises and much more.Links Mentioned in the Show:BoomiSteve’s Book - Digital Impact: The Human Element of AI-Driven TransformationWhat is the OSI Model?Connect with SteveSkill Track: AI Business FundamentalsRelated Episode: New Models for Digital Transformation with Alison McCauley Chief Advocacy Officer at Think with AI & Founder of Unblocked FutureRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Business intelligence has been transforming organizations for decades, yet many companies still struggle with widespread adoption. With less than 40% of employees in most organizations having access to BI tools, there's a significant 'information underclass' making decisions without data-driven insights. How can businesses bridge this gap and achieve true information democracy? While new technologies like generative AI and semantic layers offer promising solutions, the fundamentals of data quality and governance remain critical. What balance should organizations strike between investing in innovative tools and strengthening their data infrastructure? How can you ensure your business becomes a 'data athlete' capable of making hyper-decisive moves in an uncertain economic landscape?Howard Dresner is founder and Chief Research Officer at Dresner Advisory Services and a leading voice in Business Intelligence (BI), credited with coining the term “Business Intelligence” in 1989. He spent 13 years at Gartner as lead BI analyst, shaping its research agenda and earning recognition as Analyst of the Year, Distinguished Analyst, and Gartner Fellow. He also led Gartner’s BI conferences in Europe and North America. Before founding Dresner Advisory in 2007, Howard was Chief Strategy Officer at Hyperion Solutions, where he drove strategy and thought leadership, helping position Hyperion as a leader in performance management prior to its acquisition by Oracle. Howard has written two books, The Performance Management Revolution – Business Results through Insight and Action, and Profiles in Performance – Business Intelligence Journeys and the Roadmap for Change - both published by John Wiley & Sons.In the episode, Richie and Howard explore the surprising low penetration of business intelligence in organizations, the importance of data governance and infrastructure, the evolving role of AI in BI, and the strategic initiatives driving BI usage, and much more.Links Mentioned in the Show:Dresner Advisory ServicesHoward’s Book - Profiles in Performance: Business Intelligence Journeys and the Roadmap for ChangeConnect with HowardSkill Track: Power BI FundamentalsRelated Episode: The Next Generation of Business Intelligence with Colin Zima, CEO at OmniRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Technology and human consciousness are converging in ways that challenge our fundamental understanding of creativity and connection. As AI systems become increasingly sophisticated at mimicking human thought patterns, we're entering uncharted territory where machines don't just assist creative work—they actively participate in it. But what does this mean for the future of human creativity and our relationship with technology? How do we maintain meaningful human connections in a world where emotional labor is increasingly commoditized? As we navigate this rapidly evolving landscape, the question isn't just whether machines can think, but how their thinking will transform our own.Ken Liu is an American author of speculative fiction. A winner of the Nebula, Hugo, and World Fantasy awards, he wrote the Dandelion Dynasty, a silkpunk epic fantasy series, as well as short story collections The Paper Menagerie and Other Stories and The Hidden Girl and Other Stories. His latest book is All that We See or Seem, a techno-thriller starring an AI-whispering hacker who saves the world. He also translated Cixin Liu’s seminal book series, the Three-Body Problem. He’s often involved in media adaptations of his work. Recent projects include “The Regular,” under development as a TV series; “Good Hunting,” adapted as an episode in season one of Netflix’s breakout adult animated series Love, Death + Robots; and AMC’s Pantheon, with Craig Silverstein as executive producer, adapted from an interconnected series of Liu’s short stories. Prior to becoming a full-time writer, Liu worked as a software engineer, corporate lawyer, and litigation consultant. Liu frequently speaks on a variety of topics, including futurism, machine-augmented creativity, history of technology, bookmaking, and the mathematics of origami.In the episode, Adel and Ken explore the intersection of technology and storytelling, how sci-fi can inform AI's trajectory, the role of AI in reshaping human relationships and creativity, how AI is changing art, and much more.Links Mentioned in the Show:Ken’s BooksKen on Substack, Ken on XSkill Track: AI FundamentalsRelated Episode: What History Tells Us About the Future of AI with Verity Harding, Author of AI Needs YouRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Welcome to DataFramed Industry Roundups! In this series of episodes, we sit down to discuss the latest and greatest in data & AI. In this episode, with special guest, DataCamp COO Martijn, we touch upon the hype and reality of AI agents in business, the McKinsey vs. Ethan Mollick debate on simple vs. complex agents, Meta's $15B stake in Scale AI and what it means for data and talent, Apple’s rumored $20B bid for Perplexity amid AI struggles, EU’s push to treat AI skills like reading and math, the first fully AI-generated NBA ad and what it means for creative industries, a new benchmark for deep research tools, and much more.Links Mentioned in the Show:Meta bought Scale AIApple rumoured to buy trying to acquire Perplexity for $20BnMcKinsey's Seizing the Agentic AI Advantage reportThe first fully AI-generated NBA AdEU Generative AI Outlook reportMary Meeker's Trend in AI reportDeep research benchmarkRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The enterprise adoption of AI agents is accelerating, but significant challenges remain in making them truly reliable and effective. While coding assistants and customer service agents are already delivering value, more complex document-based workflows require sophisticated architectures and data processing capabilities. How do you design agent systems that can handle the complexity of enterprise documents with their tables, charts, and unstructured information? What's the right balance between general reasoning capabilities and constrained architectures for specific business tasks? Should you centralize your agent infrastructure or purchase vertical solutions for each department? The answers lie in understanding the fundamental trade-offs between flexibility, reliability, and the specific needs of your organization.Jerry Liu is the CEO and Co-founder at LlamaIndex, the AI agents platform for automating document workflows. Previously, he led the ML monitoring team at Robust Intelligence, did self-driving AI research at Uber ATG, and worked on recommendation systems at Quora.In the episode, Richie and Jerry explore the readiness of AI agents for enterprise use, the challenges developers face in building these agents, the importance of document processing and data structuring, the evolving landscape of AI agent frameworks like LlamaIndex, and much more.Links Mentioned in the Show:LlamaIndexLlamaIndex Production Ready Framework For LLM AgentsTutorial: Model Context Protocol (MCP)Connect with JerryCourse: Retrieval Augmented Generation (RAG) with LangChainRelated Episode: RAG 2.0 and The New Era of RAG Agents with Douwe Kiela, CEO at Contextual AI & Adjunct Professor at Stanford UniversityRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The line between generic AI capabilities and truly transformative business applications often comes down to one thing: your data. While foundation models provide impressive general intelligence, they lack the specialized knowledge needed for domain-specific tasks that drive real business value. But how do you effectively bridge this gap? What's the difference between simply fine-tuning models versus using techniques like retrieval-augmented generation? And with constantly evolving models and technologies, how do you build systems that remain adaptable while still delivering consistent results? Whether you're in retail, healthcare, or transportation, understanding how to properly enrich, annotate, and leverage your proprietary data could be the difference between an AI project that fails and one that fundamentally transforms your business.Wendy Gonzalez is the CEO — and former COO — of Sama, a company leading the way in ethical AI by delivering accurate, human-annotated data while advancing economic opportunity in underserved communities. She joined Sama in 2015 and has been central to scaling both its global operations and its mission-driven business model, which has helped over 65,000 people lift themselves out of poverty through dignified digital work. With over 20 years of experience in the tech and data space, Wendy’s held leadership roles at EY, Capgemini, and Cycle30, where she built and managed high-performing teams across complex, global environments. Her leadership style blends operational excellence with deep purpose — ensuring that innovation doesn’t come at the expense of integrity. Wendy is also a vocal advocate for inclusive AI and sustainable impact, regularly speaking on how companies can balance cutting-edge technology with real-world responsibility.Duncan Curtis is the Senior Vice President of Generative AI at Sama, where he leads the development of AI-powered tools that are shaping the future of data annotation. With a background in product leadership and machine learning, Duncan has spent his career building scalable systems that bridge cutting-edge technology with real-world impact. Before joining Sama, he led teams at companies like Google, where he worked on large-scale personalization systems, and contributed to AI product strategy across multiple sectors. At Sama, he's focused on harnessing the power of generative AI to improve quality, speed, and efficiency — all while keeping human oversight and ethical practices at the core. Duncan brings a unique perspective to the AI space: one that’s grounded in technical expertise, but always oriented toward practical solutions and responsible innovation.In the episode, Richie, Wendy, and Duncan explore the importance of using specialized data with large language models, the role of data enrichment in improving AI accuracy, the balance between automation and human oversight, the significance of responsible AI practices, and much more.Links Mentioned in the Show:SamaConnect with WendyConnect with DuncanCourse: Generative AI ConceptsRelated Episode: Creating High Quality AI Applications with Theresa Parker & Sudhi Balan, Rocket SoftwareRegister for RADAR AINew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The modern data stack has transformed how organizations work with data, but are our BI tools keeping pace with these changes? As data schemas become increasingly fluid and analysis needs range from quick explorations to production-grade reporting, traditional approaches are being challenged. How can we create analytics experiences that accommodate both casual spreadsheet users and technical data modelers? With semantic layers becoming crucial for AI integration and data governance growing in importance, what skills do today's BI professionals need to master? Finding the balance between flexibility and governance is perhaps the greatest challenge facing data teams today.Colin Zima is the Co-Founder and CEO of Omni, a business intelligence platform focused on making data more accessible and useful for teams of all sizes. Prior to Omni, he was Chief Analytics Officer and VP of Product at Looker, where he helped shape the product and data strategy leading up to its acquisition by Google for $2.6 billion. Colin’s background spans roles in data science, analytics, and product leadership, including positions at Google, HotelTonight, and as founder of the restaurant analytics startup PrimaTable. He holds a degree in Operations Research and Financial Engineering from Princeton University and began his career as a Structured Credit Analyst at UBS.In the episode, Richie and Colin explore the evolution of BI tools, the challenges of integrating casual and rigorous data analysis, the role of semantic layers, and the impact of AI on business intelligence. They discuss the importance of understanding business needs, creating user-focused dashboards, and the future of data products, and much more.Links Mentioned in the Show:OmniConnect with ColinSkill Track: Design in Power BIRelated Episode: Self-Service Business Intelligence with Sameer Al-Sakran, CEO at MetabaseRegister for RADAR AI - June 26New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Retrieval Augmented Generation (RAG) continues to be a foundational approach in AI despite claims of its demise. While some marketing narratives suggest RAG is being replaced by fine-tuning or long context windows, these technologies are actually complementary rather than competitive. But how do you build a truly effective RAG system that delivers accurate results in high-stakes environments? What separates a basic RAG implementation from an enterprise-grade solution that can handle complex queries across disparate data sources? And with the rise of AI agents, how will RAG evolve to support more dynamic reasoning capabilities?Douwe Kiela is the CEO and co-founder of Contextual AI, a company at the forefront of next-generation language model development. He also serves as an Adjunct Professor in Symbolic Systems at Stanford University, where he contributes to advancing the theoretical and practical understanding of AI systems.Before founding Contextual AI, Douwe was the Head of Research at Hugging Face, where he led groundbreaking efforts in natural language processing and machine learning. Prior to that, he was a Research Scientist and Research Lead at Meta’s FAIR (Fundamental AI Research) team, where he played a pivotal role in developing Retrieval-Augmented Generation (RAG)—a paradigm-shifting innovation in AI that combines retrieval systems with generative models for more grounded and contextually aware responses.In the episode, Richie and Douwe explore the misconceptions around the death of Retrieval Augmented Generation (RAG), the evolution to RAG 2.0, its applications in high-stakes industries, the importance of metadata and entitlements in data governance, the potential of agentic systems in enterprise settings, and much more.Links Mentioned in the Show:Contextual AIConnect with DouweCourse: Retrieval Augmented Generation (RAG) with LangChainRelated Episode: High Performance Generative AI Applications with Ram Sriharsha, CTO at PineconeRegister for RADAR AI - June 26New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

GPU acceleration is transforming how data scientists tackle computationally intensive problems in the AI and materials science fields. When dealing with billions of potential molecular combinations or massive datasets requiring dimensionality reduction, traditional CPU approaches often become prohibitively slow and expensive. How can data professionals determine when GPU acceleration will provide meaningful benefits to their workflows? Understanding the right applications for this technology can mean the difference between waiting hours versus minutes for critical results.Nick Becker is a Group Product Manager at NVIDIA, focused on building RAPIDS and the broader accelerated data science ecosystem. Nick has a professional background in technology and government. Prior to NVIDIA, he worked at Enigma Technologies, a data science startup. Before Enigma, he conducted economics research and forecasting at the Federal Reserve Board of Governors, the central bank of the United States.Dan Hannah is an Associate Director at SES AI Corporation. At SES, Dan leads a research program focused on discovering new battery materials using machine learning, chemical informatics, and physics-driven simulations. Prior to joining SES, Dan spent several years as a data scientist in the cybersecurity industry. Dan holds a Ph.D. in Physical Chemistry from Northwestern University and did a postdoctoral fellowship at Berkeley National Lab, where his focus was the discovery of novel inorganic materials for energy applications.In the episode, Richie, Nick, and Dan explore the quest for new battery technologies, the role of data science and machine learning in material discovery, the integration of NVIDIA's GPU technology, the balance between computational simulations and lab work, and much more.Links Mentioned in the Show:NVIDIA RAPIDSSES AI CorporationConnect with Dan and NickCareer Track: Machine Learning Scientist in PythonRelated Episode: Data Science Trends from 2 Kaggle Grandmasters with Jean-Francois Puget, Distinguished Engineer at NVIDIA & Chris Deotte, Senior Data Scientist at NVIDIARewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

AI maturity isn't achieved through technology alone—it requires organizational alignment, cultural readiness, and strategic implementation. Companies across industries are working to move beyond experimental AI use toward systematic integration that delivers measurable business value. How do you assess where your organization stands on the AI maturity spectrum? What frameworks can help prioritize your efforts?Eryn Peters, Co-founder & co-creator at AI Maturity Index, is a future of work evangelist. She is the co-creator of a tool for assessing AI maturity, and regularly advises companies on how to assess and improve their AI maturity. Eryn is also the Editor of the Weekly Workforce newsletter and the Principal at the Startup Consortium consultancy. Previously, she was the Global Director of the Association for the Future of Work, and VP of Marketing at Andela.Iwo Szapar is a serial entrepreneur with a passion for creating impactful solutions that enable people to work smarter, not harder. He is the co-founder of several innovative initiatives, including Remote-how, Remote-First Institute, AI-Mentor, and the Saudi AI Leadership Forum. Throughout his career, Iwo has helped transform how over 3,000 companies—including Microsoft, Walmart, and ING Bank—approach the future of work.In the episode, Richie, Eryn, and Iwo explore AI maturity in organizations, the balance between top-down and bottom-up AI adoption, the relationship between data and AI maturity, the importance of change management, practical steps for AI implementation, and much more.Links Mentioned in the Show:AI Maturity IndexEryn’s WebsiteIwo’s Book: Remote Work Is The WayConnect with Eryn and IwoState of Data & AI Literacy Report 2025Eryn’s previous webinar: Assessing Your Organization's AI MaturityRelated Episode: Scaling Responsible AI Literacy with Uthman Ali, Global Head of Responsible AI at BPRewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

AI tooling continues to expand with specialized solutions for every step of the development process. For data scientists and engineers, this creates a paradox: more options but potentially more complexity and integration challenges. How do you determine which tools actually improve productivity versus adding unnecessary overhead? Should you prioritize flexibility with individual best-of-breed components or streamline with integrated platforms? What's the most effective way to bridge the gap between experimentation and production-ready AI applications?William Falcon is an AI researcher and the CEO of Lightning AI. He is the creator of PyTorch Lightning, a lightweight framework designed for training models of any size. As the founder of Lightning AI, he leads the development of Lightning AI Studios and the AI Hub. Falcon also shares his expertise in AI research and machine learning engineering through educational content on YouTube and X (formerly Twitter). He is passionate about leveraging AI for social impact.In the episode, Richie and William explore the NY AI hub, the journey from AI idea to production, diverse perspectives in AI development, how Lightning AI simplifies AI workflows, the significance of open-source models, and much more.Links Mentioned in the Show:Lightning AIPyTorch LightningConnect with WilliamCourse: Introduction to Deep Learning in PyTorch CourseRelated Episode: Building Multi-Modal AI Applications with Russ d'Sa, CEO & Co-founder of LiveKitRewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The like button has transformed how we interact online, becoming a cornerstone of digital engagement with over 7 billion clicks daily. What started as a simple user interface solution has evolved into a powerful data collection tool that companies use to understand customer preferences, predict trends, and build sophisticated recommendation systems. The data behind these interactions forms what experts call the 'like graph' - a valuable network of connections that might be one of your company's most underutilized assets.Bob Goodson is President and Founder of Quid, a Silicon Valley–based company whose AI models are used by a third of the Fortune 50. Before starting Quid, he was the first employee at Yelp, where he played a role in the genesis of the like button and observed firsthand the rise of the social media industry. After Quid received an award in 2016 from the World Economic Forum for “Contributions to the Future of the Internet,” Bob served a two-year term on WEF’s Global Future Council for Artificial Intelligence & Robotics. While at Oxford University doing graduate research in language theory, Bob co-founded Oxford Entrepreneurs to connect scientists with business-minded students. Bob is co-author of a new book, Like: The Button That Changed the World, focussed on the origins of the ubiquitous Like Button in social media.In the episode, Richie and Bob explore the origins of the like button, its impact on user interaction and business, the evolution of social media features, the significance of relational data, and the future of social networks in the age of AI, and much more.Links Mentioned in the Show:Bob’s book—Like: The Button That Changed the WorldConnect with BobCourse: Analyzing Social Media Data in PythonRelated Episode: How I Nearly Got Fired For Running An A/B Test with Vanessa Larco, Former Partner at New Enterprise AssociatesRewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Welcome to DataFramed Industry Roundups! In this series of episodes, Adel & Richie sit down to discuss the latest and greatest in data & AI. In this episode, we touch upon the launch of OpenAI’s O3 and O4-mini models, Meta’s rocky release of Llama 4, Google’s new agent tooling ecosystem, the growing arms race in AI, the latest from the Stanford AI Index report, the plausibility of AGI and superintelligence, how agents might evolve in the enterprise, global attitudes toward AI, and a deep dive into the speculative—but chilling—AI 2027 scenario. All that, Easter rave plans, and much more.Links Mentioned in the Show:Introducing OpenAI o3 and o4-miniThe Median: Scaling Models or Scaling People? Llama 4, A2A, and the State of AI in 2025LLama 4Google: Announcing the Agent2Agent Protocol (A2A)Stanford University's Human Centered AI Institute Releases 2025 AI Index ReportAI 2027Rewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The roles within AI engineering are as diverse as the challenges they tackle. From integrating models into larger systems to ensuring data quality, the day-to-day work of AI professionals is anything but routine. How do you navigate the complexities of deploying AI applications? What are the key steps from prototype to production? For those looking to refine their processes, understanding the full lifecycle of AI development is essential. Let's delve into the intricacies of AI engineering and the strategies that lead to successful implementation.Maxime Labonne is a Senior Staff Machine Learning Scientist at Liquid AI, serving as the head of post-training. He holds a Ph.D. in Machine Learning from the Polytechnic Institute of Paris and is recognized as a Google Developer Expert in AI/ML. An active blogger, he has made significant contributions to the open-source community, including the LLM Course on GitHub, tools such as LLM AutoEval, and several state-of-the-art models like NeuralBeagle and Phixtral. He is the author of the best-selling book “Hands-On Graph Neural Networks Using Python,” published by Packt.Paul-Emil Iusztin designs and implements modular, scalable, and production-ready ML systems for startups worldwide. He has extensive experience putting AI and generative AI into production. Previously, Paul was a Senior Machine Learning Engineer at Metaphysic.ai and a Machine Learning Lead at Core.ai. He is a co-author of The LLM Engineer's Handbook, a best seller in the GenAI space.In the episode, Richie, Maxime, and Paul explore misconceptions in AI application development, the intricacies of fine-tuning versus few-shot prompting, the limitations of current frameworks, the roles of AI engineers, the importance of planning and evaluation, the challenges of deployment, and the future of AI integration, and much more.Links Mentioned in the Show:Maxime’s LLM Course on HuggingFaceMaxime and Paul’s Code Alongs on DataCampDecoding ML on SubstackConnect with Maxime and PaulSkill Track: AI FundamentalsRelated Episode: Building Multi-Modal AI Applications with Russ d'Sa, CEO & Co-founder of LiveKitRewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Data-driven turnarounds are transforming how struggling businesses find their path back to profitability. When companies falter, the key to recovery can often lies in understanding which 20% of customers and products generate 80% of profits. But how do you quickly identify these critical assets when time is running out? What metrics should you prioritize when cash flow is tight? For data professionals, the challenge extends beyond analysis to implementation—balancing the need for automation of routine tasks while reskilling employees for higher-value work. The intersection of empathy and analytics becomes crucial as teams navigate the emotional journey of organizational change while making tough decisions based on hard numbers.Bill Canady is CEO at Arrowhead Engineered Products and a global business executive with over 30 years of experience across a range of industries. Bill is known for aligning with stakeholders to establish clear, growth-oriented strategies, as well as leading global public, private, and private equity-owned companies by building strong leadership teams and fostering deep relationships. As the former CEO of OTC Industrial Technologies, he oversaw $1 billion in annual sales. Under his leadership, OTC achieved over 43% revenue growth and a 78% increase in earnings. Throughout his career, Bill has guided organizations through complex challenges in regulatory, investor, and media landscapes. Drawing on his extensive experience, he developed the Profitable Growth Operating System (PGOS) to help business leaders worldwide drive sustainable, profitable growth.In the episode, Richie and Bill explore the journey from panic to profit in failing companies, the 100-day turnaround process, leveraging data for decision-making, the Pareto principle in business, automation's role in efficiency, and the importance of empathy and continuous learning in leadership, and much more.Links Mentioned in the Show:Bill’s new book: From Panic to ProfitThe 80/20 CEO by Bill CanadyConnect with BillBill’s websiteSkill Track: AI LeadershipRelated Episode: Leadership in the AI Era with Dana Maor, Senior Partner at McKinsey & CompanySign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

We live in an era where data is abundant, yet making sense of it is harder than ever. The best insights often go unnoticed—not because they lack value, but because they lack a compelling story. Simply presenting numbers isn’t enough; the way we shape and frame data determines whether it sparks action or fades into the background. Crafting a strong data story means knowing your audience, structuring your insights around a clear problem, goal, action, and impact, and ensuring your narrative is not just persuasive, but ethical. So how do we bridge the gap between information and understanding? How can we tailor data stories to resonate with decision-makers, stakeholders, and the public in ways that drive meaningful change?Kat Greenbrook is a Data Storyteller from Aotearoa, New Zealand. She is a consultant, workshop facilitator, industry speaker, and founder of the data storytelling company Rogue Penguin Ltd. With a unique blend of science, business, and design, she empowers data professionals to communicate data effectively through storytelling. Kat’s book, The Data Storyteller's Handbook, is the result of hundreds of data storytelling workshops, along with years of refining content and techniques. It represents the very best of what she has learned and witnessed.In the episode, Richie and Kat explore the art of data storytelling, the importance of audience-tailored narratives, the problem-goal-action-impact framework, ethical storytelling, and much more.Links Mentioned in the Show:Kat’s Book: The Data Storyteller's HandbookConnect with KatCourse: Data Storytelling ConceptsRelated Episode: Data Storytelling and Visualization with Lea Pica from Present Beyond MeasureRewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Misconceptions about AI's capabilities and the role of data are everywhere. Many believe AI is a singular, all-knowing entity, when in reality, it's a collection of algorithms producing intelligence-like outputs. Navigating and understanding the history and evolution of AI, from its origins to today's advanced language models is crucial. How do these developments, and misconceptions, impact your daily work? Are you leveraging the right tools for your needs, or are you caught up in the allure of cutting-edge technology without considering its practical application?Andriy Burkov is the author of three widely recognized books, The Hundred-Page Machine Learning Book, The Machine Learning Engineering Book, and recently The Hundred-Page Language Models book. His books have been translated into a dozen languages and are used as textbooks in many universities worldwide. His work has impacted millions of machine learning practitioners and researchers. He holds a Ph.D. in Artificial Intelligence and is a recognized expert in machine learning and natural language processing. As a machine learning expert and leader, Andriy has successfully led dozens of production-grade AI projects in different business domains at Fujitsu and Gartner. Andriy is currently Machine Learning Lead at TalentNeuron.In the episode, Richie and Andriy explore misconceptions about AI, the evolution of AI from the 1950s, the relevance of 20th-century AI research, the role of linear algebra in AI, the resurgence of recurrent neural networks, advancements in large language model architectures, the significance of reinforcement learning, the reality of AI agents, and much more.Links Mentioned in the Show:Andriy’s books: The Hundred-page Machine Learning Book, The Hundred-page Language Models BookTalentNeuronConnect with AndriySkill Track: AI FundamentalsRelated Episode: Unlocking Humanity in the Age of AI with Faisal Hoque, Founder and CEO of SHADOKARewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The explosion of content in market research has created a paradox - more information but less time to consume it. Companies are now turning to AI chatbots to solve this problem, transforming how professionals interact with research data. Instead of expecting teams to read everything, these tools allow users to extract precisely what they need when they need it. This approach is proving not just more efficient but actually increases engagement with underlying content. How might your organization benefit from more targeted access to insights? What valuable information might be buried in your existing research that AI could help surface?With over 30 years of experience in marketing, media, and technology, Dan Coates is the President and co-founder of YPulse, the leading authority on Gen Z and Millennials. YPulse helps brands like Apple, Netflix, and Xbox understand and communicate with consumers aged 13–39, using data and insights from over 400,000 interviews conducted annually across seven countries. Prior to founding YPulse, Dan co-founded SurveyU, an online community and insights platform targeting youth, which merged with YPulse in 2009. He also led the introduction of Globalpark’s SAAS platform into the North American market, until its acquisition by QuestBack in 2011. In addition, Dan has held senior roles at Polimetrix, SPSS, PlanetFeedback, and Burke, where he developed cutting-edge practices and products for online marketing insights and transitioned several ventures from early stages to high-value acquisitions.In the episode, Richie and Dan explore the creation of an AI chatbot for market research, addressing customer engagement challenges, the integration of AI in content consumption, the impact of AI on business strategies, and the future of AI in market research, and much more.Links Mentioned in the Show:YPulseConnect with DanHaystack by DeepsetUnmanaged: Master the Magic of Creating Empowered and Happy Organizations by Jack SkeelsSkill Track: AI FundamentalsRelated Episode: Can You Use AI-Driven Pricing Ethically? with Jose Mendoza, Academic Director & Clinical Associate Professor at NYURewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The role of data and AI engineers is more critical than ever. With organizations collecting massive amounts of data, the challenge lies in building efficient data infrastructures that can support AI systems and deliver actionable insights. But what does it take to become a successful data or AI engineer? How do you navigate the complex landscape of data tools and technologies? And what are the key skills and strategies needed to excel in this field? Deepak Goyal is a globally recognized authority in Cloud Data Engineering and AI. As the Founder & CEO of Azurelib Academy, he has built a trusted platform for advanced cloud education, empowering over 100,000 professionals and influencing data strategies across Fortune 500 companies. With over 17 years of leadership experience, Deepak has been at the forefront of designing and implementing scalable, real-world data solutions using cutting-edge technologies like Microsoft Azure, Databricks, and Generative AI.In the episode, Richie and Deepak explore the fundamentals of data engineering, the critical skills needed, the intersection with AI roles, career paths, and essential soft skills. They also discuss the hiring process, interview tips, and the importance of continuous learning in a rapidly evolving field, and much more.Links Mentioned in the Show:AzureLibAzureLib Academy Connect with DeepakGet Certified! Azure FundamentalsRelated Episode: Effective Data Engineering with Liya Aizenberg, Director of Data Engineering at AwaySign up to attend RADAR: Skills Edition New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As data professionals, mastering the technical aspects of AI and data is only half the battle. The real challenge lies in effectively communicating insights to drive action and influence decisions. How do you ensure your data stories resonate with diverse audiences? It's not just about the numbers—it's about crafting a narrative that speaks to stakeholders. What strategies can you employ to make your insights not only heard but impactful?Abhijit Bhaduri advises organizations on talent and leadership development. As the former Partner and GM Global L&D of Microsoft, Abhijit led their onboarding and skilling strategy especially for people managers. Forbes described him as "the most interesting generalist from India." The San Francisco Examiner described him as the "world’s foremost expert on talent and development" and among the ten most sought-after brand evangelists. Abhijit also teaches in the Doctoral Program for Chief Learning Officers at the University of Pennsylvania. Prior to being at Microsoft, he led an advisory practice helping organizations build their leadership, talent and culture strategy. His latest book is called "Career 3.0 – Six Skills You Must Have To Succeed."In the episode, Richie and Abhijit explore the complexities of modern career paths, the importance of experimentation and adaptability, the evolution of career models from 1.0 to 3.0, the impact of longevity on career strategies, essential skills for career advancement, and much more.Links Mentioned in the Show:Abhijit’s newsletter on Linkedin - Dreamers and Unicorns Abhijit’s Book - Career 3.0 – Six Skills You Must Have To SucceedConnect with AbhijitSkill Track: AI FundamentalsRelated Episode: Career Skills for Data Professionals with Wes Kao, Co-Founder of MavenSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The integration of AI into everyday business operations raises questions about the future of work and human agency. With AI's potential to automate and optimize, how do we ensure that it complements rather than competes with human capabilities? What measures can be taken to prevent AI from overshadowing human input and creativity? How do we strike a balance between embracing AI's benefits and preserving the essence of human contribution?Faisal Hoque is the founder and CEO of SHADOKA, NextChapter, and other companies. He also serves as a transformation and an innovation partner for CACI, an $8B company focused on U.S. national security. He volunteers for several organizations, including MIT IDEAS Social Innovation Program. He is also a contributor at the Swiss business school IMD, Thinkers50, the Project Management Institute (PMl), and others. As a founder and CEO of multiple companies, he is a three-time winner of Deloitte Technology Fast 50™ and Fast 500™ awards. He has developed more than 20 commercial platforms and worked with leadership at the U.S. DoD, DHS, GE, MasterCard, American Express, Home Depot, PepsiCo, IBM, Chase, and others. For their innovative work, he and his team have been awarded several provisional patents in the areas of user authentication, business rule routing, and metadata sorting.In the episode, Richie and Faisal explore the philosophical implications of AI on humanity, the concept of AI as a partner, the potential societal impacts of AI-driven unemployment, the importance of critical thinking and personal responsibility in the AI era, and much more.Links Mentioned in the Show:SHADOKAFaisail’s WebsiteConnect with FaisalSkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: Making Better Decisions using Data & AI with Cassie Kozyrkov, Google's First Chief Decision ScientistSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

In the retail industry, data science is not just about crunching numbers—it's about driving business impact through well-designed experiments. A-B testing in a physical store setting presents unique challenges that require careful planning and execution. How do you balance the need for statistical rigor with the practicalities of store operations? What role does data science play in ensuring that test results lead to actionable insights? Philipp Paraguya is the Chapter Lead for Data Science at Aldi DX. Previously, Philipp studied applied mathematics and computer science and has worked as a BI and advanced analytics consultant in various industries and projects since graduating. Due to his background as a software developer, he has a strong connection to classic software engineering and the sensible use of data science solutions.In the episode, Adel and Philipp explore the intricacies of A-B testing in retail, the challenges of running experiments in brick-and-mortar settings, aligning stakeholders for successful experimentation, the evolving role of data scientists, the impact of genAI on data workflows, and much more.Links Mentioned in the Show:Aldi DXConnect with PhilippCourse: Customer Analytics and A/B Testing in PythonRelated Episode: Can You Use AI-Driven Pricing Ethically? with Jose Mendoza, Academic Director & Clinical Associate Professor at NYUSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The integration of speech AI into everyday business operations is reshaping how we communicate and process information. With applications ranging from customer service to quality control, understanding the nuances of speech AI is crucial for professionals. How do you tackle the complexities of different languages and accents? What are the best practices for implementing speech AI in your organization? Explore the transformative power of speech AI and learn how to overcome the challenges it presents in your professional landscape.Alon Peleg serves as the Chief Operating Officer (COO) at aiOla, a position he assumed in May 2024. With over two decades of leadership experience at renowned companies like Wix, Cisco, and Intel, he is widely recognized in the tech industry for his expertise, dynamic leadership, and unwavering dedication. At aiOla, Alon plays a key role in driving innovation and strategic growth, contributing to the company’s mission of developing cutting-edge solutions in the tech space. His appointment is regarded as a pivotal step in aiOla’s expansion and continued success.Gill Hetz is the VP of AI at aiOla where he leverages his expertise in data integration and modeling. Gill was previously active in the oil and gas industry since 2009, holding roles in engineering, research, and data science. From 2018 to 2021, Gill held key positions at QRI, including Project Manager and SaaS Product Manager.In the episode, Richie, Alon, and Gill explore the intricacies of speech AI, its components like ASR, NLU, and TTS, real-world applications in industries such as retail and pharmaceuticals, challenges like accents and background noise, and the future of voice interfaces in technology, and much more.Links Mentioned in the Show:aiOlaConnect with Alon and GillCourse: Spoken Language Processing in PythonRelated Episode: Building Multi-Modal AI Applications with Russ d'Sa, CEO & Co-founder of LiveKitSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The rise of AI tools has democratized access to technology, but with it comes the responsibility to use these tools ethically. How do organizations ensure their employees are not only aware of AI's capabilities but also its risks? What does it mean to have a responsible AI strategy that is both comprehensive and adaptable to future advancements? As companies strive to align their AI initiatives with ethical standards, what are the best practices for training and upskilling teams to meet these challenges head-on?Uthman Ali is the Global Head of Responsible AI at BP and is an expert on AI ethics. As a former human rights lawyer and neuro-ethicist, he recognized how regulations were not keeping up with the pace of innovation and specialized in this emerging field. Some of his current projects include creating ethical policies/procedures for the use of robots, wearables and using AI for creativity.In the episode, Adel and Uthman explore the importance of responsible AI in organizations, the critical role of upskilling, the impact of the EU AI Act, practical implementation of AI ethics, the spectrum of AI skills needed, the future of AI governance, and much more.Links Mentioned in the Show:Report: The State of Data & AI LiteracyConnect with UthmanCourse: Responsible AI PracticesRelated Episode: Scaling AI in the Enterprise with Abhas Ricky, Chief Strategy Officer at ClouderaSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The rise of A-B testing has transformed decision-making in tech, yet its application isn't without challenges. As professionals, how do you navigate the balance between short-term gains and long-term sustainability? What strategies can you employ to ensure your testing methods enhance rather than hinder user experience? And how do you effectively communicate the insights gained from testing to drive meaningful change within your organization?Vanessa Larco is a former partner at NEA where she led Series A and Series B investment rounds and worked with major consumer companies like DTC jewelry giant Mejuri, menopause symptom relief treatment Evernow, and home-swapping platform Kindred as well as major enterprise SaaS companies like Assembled, Orby AI, Granica AI, EvidentID, Rocket.Chat, Forethought AI. She is also a board observer at Forethought, SafeBase, Orby AI, Granica, Modyfi, and HEAVY.AI. She was a board observer at Robinhood until its IPO in 2021. Before she became an investor, she built consumer and enterprise tech herself at Microsoft, Disney, Twilio, and Box as a product leader.In the episode, Richie and Vanessa explore the evolution of A-B testing in gaming, the balance between data-driven decisions and user experience, the challenges of scaling experimentation, the pitfalls of misaligned metrics, the importance of understanding user behavior, and much more.Links Mentioned in the Show:New Enterprise AssociatesConnect with VanessaCourse: Customer Analytics and A/B Testing in PythonRelated Episode: Make Your A/B Testing More Effective and EfficientSign up to attend RADAR: Skills Edition - Vanessa will be speaking!New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Generative AI has transformed the financial services sector, sparking interest at all organizational levels. As AI becomes more accessible, professionals are exploring its potential to enhance their work. How can AI tools improve personalization and fraud detection? What efficiencies can be gained in product development and internal processes? These are the questions driving the adoption of AI as companies strive to innovate responsibly while maximizing value.Andrew serves as the Chief Data Officer for Mastercard, leading the organization’s data strategy and innovation efforts while navigating current and future data risks. Andrews's prior roles at Mastercard include Senior Vice President, Data Management, in which he was responsible for the quality, collection, and use of data for Mastercard’s information services and advisory business, and Mastercard’s Deputy Chief Privacy Officer, in which he was responsible for privacy and data protection issues globally for Mastercard. Andrew also spent many years as a Privacy & Intellectual Property Council advising direct marketing services, interactive advertising, and industrial chemicals industries.Andrew holds Juris Doctor from Columbia University School of Law and has his bachelor’s degree, cum laude, in Chemical Engineering from the University of Delaware. Andrew is a retired member of the State Bar of New York.In the episode, Adel and Andrew explore GenAI's transformative impact on financial services, the democratization of AI tools, efficiency gains in product development, the importance of AI governance and data quality, the cultural shifts and regulatory landscapes shaping AI's future, and much more.Links Mentioned in the Show:MastercardConnect with AndrewSkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: How Generative AI is Changing Leadership with Christie Smith, Founder of the Humanity Institute and Kelly Monahan, Managing Director, Research InstituteSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As businesses collect more data than ever, the question arises: is bigger always better? Companies are beginning to question whether massive datasets and complex infrastructures are truly delivering results or just adding unnecessary costs. How can you align your data strategy with your actual needs? Could focusing on smaller, more manageable datasets improve efficiency and save resources while still delivering valuable insights?Dr. Madelaine Daianu is the Head of Data & AI at Credit Karma, Inc. Before joining the company in June 2023, she served as Head of Data and Pricing at Belong Home, Inc. Earlier in her career, Daianu has held numerous senior roles in data science and machine learning at The RealReal, Facebook, and Intuit. Daianu earned a Bachelor of Applied Science in Bioengineering and Mathematics from the University of Illinois at Chicago and a Ph.D. in Bioengineering and Biomedical Engineering from the University of California, Los Angeles.In the episode, Richie and Madelaine explore generative AI applications at Credit Karma, the importance of data infrastructure, the role of explainability in fintech, strategies for scaling AI processes, and much more.Links Mentioned in the Show:Credit KarmaConnect with MaddieSkill Track: AI Business FundamentalsRelated Episode: Effective Product Management for AI with Marily Nika, Gen AI Product Lead at Google AssistantSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

With AI agents and GPU acceleration at the forefront, data science is entering a new era of efficiency and innovation. How are AI copilots transforming the way data scientists code and solve problems? Are they a reliable partner or a source of new complexities? On the other hand, the move to GPU-accelerated data science tools is revolutionizing model training and experimentation. What does this mean for the future of data science workflows? Explore these cutting-edge developments and their impact on the industry.Jean-Francois got a PhD in machine learning in the previous millennium. Given the AI winter at the time, he worked for a while on mathematical optimization software as dev manager for CPLEX in a startup. He came back to Machine Learning when IBM acquired the startup. Since then he discovered Kaggle and became one of the best Kagglers in the world. He joined NVIDIA 5 years ago and leads the NVIDIA Kaggle Grandmaster team there.Chris Deotte is a senior data scientist at NVIDIA. Chris has a Ph.D. in computational science and mathematics with a thesis on optimizing parallel processing. Chris is a Kaggle 4x grandmaster.In the episode, Richie, Jean-Francois, and Chris explore the transformative role of AI agents in data science, the impact of GPU acceleration on workflows, the evolution of competitive data science techniques, the importance of model evaluation and communication skills, and the future of data science roles in an AI-driven world, and much more.Links Mentioned in the Show:NVIDIANVIDIA RapidsFew shot learningConnect with Jean-Francois on Linkedin and Kaggle and check out Chris on KaggleCourse: Winning a Kaggle Competition in PythonRelated Episode: Becoming a Kaggle GrandmasterSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Dashboards are everywhere in the data industry, but are they being used effectively? Many professionals find themselves creating dashboards that end up underutilized or misunderstood. The key is not just in the data presented, but in how it's communicated and used. How can you rethink your approach to dashboarding to ensure it aligns with business goals? What methods can you employ to engage users and drive meaningful actions?Lee is the President at DecisionViz, who provides training and consulting to organizations to improve their people, process, and culture around visualization and storytelling. He's a course creator for the University of Chicago, an instructor for TDWI, and an Adjunct Faculty Instructor for NYU School of Professional Studies. Lee is also a Tableau Certified Associate Consultant, 4 times Tableau Ambassador, and a long-term Tableau Partner. Previously, he was a Research Advisor for the International Institute of Analytics, the Founder of the 501c data community, and a senior manager at Nokia.In the episode, Richie and Lee explore the limitations of traditional dashboards, the importance of a product mindset in data visualization, the role of communication and standardization in analytics, the intersection of AI with dashboarding, and much more.Links Mentioned in the Show:DecisionVizConnect with LeeCourse: Understanding Data VisualizationRelated Episode: Data Storytelling and Visualization with Lea Pica from Present Beyond MeasureSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Welcome to DataFramed Industry Roundups! In this series of episodes, Adel & Richie sit down to discuss the latest and greatest in data & AI. In this episode, we discuss the rise of reasoning LLMs like DeepSeek R1 and the competition shaping the AI space, OpenAI’s Operator and the broader push for AI agents to control computers, and the implications of massive AI infrastructure investments like Project Stargate. We also touch on Google’s overlooked AI advancements, the challenges of AI adoption, the potential of Replit’s mobile app for building apps with natural language, and much more.Links Mentioned in the Show:YouTube Tutorial: Fine Tune DeepSeek R1 | Build a Medical ChatbotOpenAI Deep ResearchOpen OperatorGemini 2.0Lex Fridman Podcast Episode on DeepSeekRemoving Barriers to American Leadership in Artificial IntelligencePresident's Council of Advisors on Science and TechnologyProject Stargate announcements from OpenAI, SoftbankSam Altman's quest for $7tnReplit Mobile AppSign up to attend RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Optimization and decision intelligence are reshaping industries, from logistics to finance. But what does this mean for professionals navigating daily challenges? Whether you're scheduling employees or managing power grids, finding the optimal solution can mean the difference between success and failure. How do you leverage optimization to make smarter, data-driven decisions? And how do you ensure these solutions are embraced by your team? Join us as we delve into the practical applications of optimization in the workplace.Duke Perrucci is the CEO at Gurobi Optimization. Prior to being appointed CEO, Duke served as CRO and COO since 2018. Perrucci has over 25 years of experience in sales, marketing, and analytics roles. Before joining Gurobi, he served at Cambridge Analytica, FocusVision, and Unilever. He also spent nine years with Information Resources, Inc., where he worked across the entire PepsiCo enterprise.Dr. Ed Klotz is a Senior Mathematical Optimization Specialist at Gurobi Optimization. Klotz has over 30 years of experience in the mathematical optimization software industry. He is a technical expert who has helped customers solve some of the world’s most challenging mathematical optimization problems. Dr. Klotz works closely with Gurobi's customers to support them in implementing and utilizing mathematical optimization in their organizations. He also interacts heavily with the R&D team based on his experiences with the customers.In the episode, Richie, Duke, and Ed explore decision intelligence, optimization in various industries, the synergy between optimization and machine learning, overcoming challenges in model building, the role of large language models in democratizing optimization, and much more.Links Mentioned in the Show:Gurobi OptimizationConnect with Duke and EdSkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: Making Better Decisions using Data & AI with Cassie Kozyrkov, Google's First Chief Decision ScientistSign up to RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Thought leadership is more than just a buzzword—it's a strategic tool that can significantly influence business decisions and relationships. But what makes thought leadership effective? How do you ensure your insights are not only heard but also trusted and acted upon? What role does generative AI play in enhancing the storytelling process, and how can it be leveraged to create compelling narratives that resonate with your audience?Cindy Anderson is the Chief Marketing Officer/Global Lead for Engagement & Eminence at the IBM Institute for Business Value (IBV). She has co-authored research reports, published numerous articles, and delivered presentations on thought leadership, diversity, strategy implementation, project management, and technology to global audiences. She oversees a team of 30 editors, designers, and social media/email marketers. She is a founding board member of the Global Thought Leadership Institute at APQC, a new association that advances the practice of thought leadership.Anthony Marshall is the Chair of the Board of Advisors for The Global Thought Leadership Institute at APQC and the Senior Research Director of thought leadership at the IBM Institute for Business Value (IBV), leading the top-rated thought leadership and analysis program. He oversees a global team of 60 technology and industry experts, statisticians, economists, and analysts. Anthony conducts original thought leadership and has authored dozens of refereed articles and studies on topics including generative AI, innovation, digital and business transformation and ecosystems, open collaboration and skills.In the episode, Richie, Cindy, and Anthony explore the framework for thought leadership storytelling, the role of generative AI in thought leadership, the ROI of thought leadership, building trust and quality in research, and much more.Links Mentioned in the Show:The ROI of Thought Leadership book by Cindy and AnthonyAPQCConnect with Cindy and AnthonySkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: How Generative AI is Changing Leadership with Christie Smith, Founder of the Humanity Institute and Kelly Monahan, Managing Director, Research InstituteSign up to RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As the software landscape becomes more fragmented, the importance of product integrations continues to rise. For those working in data and engineering roles, this presents both challenges and opportunities. How do you efficiently manage and scale integrations across diverse systems? What tools and strategies can help you maintain data integrity and streamline workflows? And how can you ensure that your integration strategy aligns with broader business goals and customer expectations?Gil Feig is the Co-Founder and CTO of Merge, the leading unified API platform. Previously, Gil was the Head of Engineering at Untapped and worked as a software engineer at Wealthfront and LinkedIn. A graduate of Columbia University, he lives and works in New York City.In the episode, Richie and Gil explore the complexities of product integrations, the evolution of software ecosystems, the challenges of scaling integrations, the role of data engineers, the impact on business operations, and the future of integration technology, and much more.Links Mentioned in the Show:MergeConnect with GilCourse: Implementing AI Solutions in BusinessRelated Episode: Building Multi-Modal AI Applications with Russ d'Sa, CEO & Co-founder of LiveKitSign up to RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As AI continues to dominate industry conversations, the notion of AI readiness becomes a focal point for organizations. It's a multifaceted challenge that goes beyond technology, encompassing business processes and cultural shifts. For professionals, this means grappling with questions like: How do you choose the right AI projects that align with business goals? What skills and team structures are necessary to support AI initiatives? And how do you manage the change that comes with integrating AI into your operations?Venky Veeraraghavan is the Chief Product Officer at DataRobot. As CPO, Venky drives the definition and delivery of the DataRobot Enterprise AI Suite. Venky has twenty-five years of experience focusing on big data and AI as a product leader and technical consultant at top technology companies (Microsoft) and early-stage startups (Trilogy).In the episode, Richie and Venky Veeraraghavan explore AI readiness in organizations, the importance of aligning AI with business processes, the roles and skills needed for AI integration, the balance between building and buying AI solutions, the challenges of implementing AI-driven changes, and much more.Links Mentioned in the Show:DatarobotConnect with VenkySkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: Aligning AI with Enterprise Strategy with Leon Gordon, CEO at Onyx DataAttend RADAR Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The rise of AI agents in the workplace is transforming how businesses operate, tackling repetitive tasks and freeing up human employees for more creative endeavors. But what does this mean for the future of work, and how can professionals leverage these tools effectively? As AI agents become more sophisticated, capable of reasoning and decision-making, how do you ensure they align with your business goals? What are the implications for data privacy and security, and how do you manage the transition to a more automated workforce while maintaining human oversight?Surojit Chatterjee is the founder and CEO of Ema. Previously, he guided Coinbase through a successful 2021 IPO as its Chief Product Officer and scaled Google Mobile Ads and Google Shopping into multi-billion dollar businesses as the VP and Head of Product. Surojit holds 40 US patents and has an MBA from MIT, MS in Computer Science from SUNY at Buffalo, and B. Tech from IIT Kharagpur.In the episode, Richie and Surojit explore the transformative role of AI agents in automating repetitive business tasks, enhancing creativity and innovation, improving customer support, and redefining workplace efficiency. They discuss the potential of AI employees, data privacy concerns, and the future of AI-driven business processes, and much more.Links Mentioned in the Show:EmaConnect with SurojitSkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: How Generative AI is Changing Leadership with Christie Smith, Founder of the Humanity Institute and Kelly Monahan, Managing Director, Research InstituteAttend RADAR Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Personalization is more than a buzzword—it's a powerful tool for businesses to connect with customers on a deeper level. As data and AI technologies evolve, the ability to deliver personalized experiences becomes more accessible. But what does this mean for professionals tasked with implementing these strategies? How do you ensure that personalization efforts are both effective and respectful of customer privacy?David Edelman is a Digital and Marketing Transformation Executive Advisor, working with executives on digital and marketing transformation. He has been working in marketing and personalization since the '80s. In addition to his consultancy business, David is an Executive Teaching Fellow at Harvard Business School and a board member for several organizations. Previously, David was Chief Marketing Officer at Aetna, and a Partner at McKinsey. Forbes has repeatedly named him one of the Top 20 Most Influential Voices in Marketing, and Ad Age has named him a Top 20 Chief Marketing and Technology Officer. He is a co-author of "Personalized: Customer Strategy in the Age of AI".In this episode, Richie and David explore the power of personalization in customer experiences, the importance of understanding customer data, strategies for effective personalization, the role of AI in enhancing customer interactions, and much more.Links Mentioned in the Show:Personalized: Customer Strategy in the Age of AIConnect with DavidSkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: Can You Use AI-Driven Pricing Ethically? with Jose Mendoza, Academic Director & Clinical Associate Professor at NYURewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As multimodal AI continues to grow, professionals are exploring new skills to harness its potential. From understanding real-time APIs to navigating new application architectures, the landscape is shifting. How can developers stay ahead in this evolving field? What opportunities do AI agents present for automating tasks and enhancing productivity? And how can businesses ensure they're ready for the future of AI-driven interactions?Russ D'Sa is the CEO & Co-founder at Livekit. Russ is building the transport layer for AI computing. He founded Livekit, the company that powers voice chat for OpenAI and Character.ai. Previously, he was a Product Manager at Medium and an engineer at Twitter. He's also a serial entrepreneur, having previously founded mobile search platform Evie Labs.In the episode, Richie and Russ explore the evolution of voice AI, the challenges of building voice applications, the rise of video AI, the implications of deep fakes, the potential of AI-generated worlds, the future of AI in customer service and education, and much more.Links Mentioned in the Show:LiveKitChatGPT VoiceCourse: Developing LLM Applications with LangChainRelated Episode: Creating High Quality AI Applications with Theresa Parker & Sudhi Balan, Rocket SoftwareRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Leadership is facing unprecedented challenges in today's socio-political and economic climate. As the lines between work and personal life blur, professionals are seeking workplaces that prioritize humanity and purpose. How can leaders create environments that support employee well-being and connection? With AI's growing presence, how do we balance technological integration with maintaining a human-centered approach?Dr. Christie Smith is a renowned leadership expert, visionary thinker, and founder of The Humanity Studio, a pioneering research and advisory institute dedicated to improving the way we live by revolutionizing the way we work. With over 35 years of experience advising Fortune 500 companies and holding global leadership roles at Accenture, Apple, and Deloitte, Dr. Smith has shaped the future of leadership, talent strategy, and organizational culture across industries.Dr. Kelly Monahan is Managing Director of the Upwork Research Institute, leading their future of work research program. Her research has been recognized and published in both applied and academic journals, including MIT Sloan Management Review and the Journal of Strategic Management. In 2018, Kelly released her first book, “How Behavioral Economics Influences Management Decision-Making: A New Paradigm” (Academic Press/Elsevier Publishers). In 2019, Kelly gave her first TedX talk on the future of work. Kelly is frequently quoted in the media on talent decision-making and the future of work. She also has written over a dozen publications and is a sought-after speaker on how to apply new management and talent models in knowledge-based organizations. Kelly holds a B.S. from Rochester Institute of Technology, an M.S. from Roberts Wesleyan College, and a Ph.D. in Organizational Leadership from Regent University.In the episode, Richie, Christie, and Kelly explore leadership transformations driven by crises, the rise of human-centered workplaces, the integration of AI with human intelligence, the evolving skill landscape, the emergence of gray-collar work, and much more.Links Mentioned in the Show:Essential: How Distributed Teams, Generative AI, and Global Shifts Are Creating a New Human-Powered LeadershipThe Humanity StudioUpwork Research InstituteConnect with Christie and KellySkill Track: AI Business FundamentalsRelated Episode: Leadership in the AI Era with Dana Maor, Senior Partner at McKinsey & CompanyRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As AI advances at breakneck speed, the conversation around its potential risks and ethical implications grows louder. For professionals in the field, this raises important questions about responsibility and foresight. How do you ensure that AI systems align with human values? What role do ethics play in the development and deployment of these technologies? Let's delve into the pressing issues that could define the future of AI and its role in society.Dr. Christopher DiCarlo is a philosopher, educator, and author. He teaches philosophy at the University of Toronto. He also founded Critical Thinking Solutions, a business consultancy, is an Expert Advisor for the Centre for Inquiry Canada, and the Ethics Chair for the Canadian Mental Health Association. His academic work focuses on bioethics and cognitive evolution. He is the author of six books, including the bestselling "How to Become a Really Good Pain in the Ass: A Critical Thinker's Guide to Asking the Right Questions", and his latest "Building a God: The Ethics of Artificial Intelligence and the Race to Control It".In the episode, Richie and Christopher explore the existential risks of powerful AI, ethical considerations in AI development, the importance of public awareness and involvement, the role of international regulation, and much more.Links Mentioned in the Show:Critical Thinking SolutionsConnect with ChristopherCourse: AI EthicsRelated Episode: Can You Use AI-Driven Pricing Ethically? with Jose Mendoza, Academic Director & Clinical Associate Professor at NYURewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As AI continues to advance, natural language processing (NLP) is at the forefront, transforming how businesses interact with data. From chatbots to document analysis, NLP offers numerous applications. But with the advent of generative AI, professionals face new challenges: When is it appropriate to use traditional NLP techniques versus more advanced models? How do you balance the costs and benefits of these technologies? Explore the strategic decisions and practical applications of NLP in the modern business world.Meri Nova is the founder of Break Into Data, a data careers company. Her work focuses on helping people switch to a career in data, and using machine learning to improve community engagement. Previously, she was a data scientist and machine learning engineer at Hyloc. Meri is the instructor of DataCamp's 'Retrieval Augmented Generation with LangChain' course.In the episode, Richie and Meri explore the evolution of natural language processing, the impact of generative AI on business applications, the balance between traditional NLP techniques and modern LLMs, the role of vector stores and knowledge graphs, and the exciting potential of AI in automating tasks and decision-making, and much more.Links Mentioned in the Show:Meri’s Breaking Into Data Handbook on GitHubBreak Into Data Discord GroupConnect with MeriSkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: Industry Roundup #2: AI Agents for Data Work, The Return of the Full-Stack Data Scientist and Old languages Make a ComebackRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

2025 promises to be another transformative year for data and AI. From groundbreaking advancements in reasoning models to the rise of new challengers in generative AI, the field shows no signs of slowing down. Last week Jonathan and Martijn scored their 2024 predictions, and scored highly, but what's in store for 2025? Building on the insights from their 2024 predictions, we'll assess the future of generative AI, the evolving role of AI in education, the growing importance of synthetic data, and much more.In the episode, Richie, Jo, and Martijn discuss whether OpenAI and Google will maintain their dominance or face disruption from new players like Meta’s Llama and XAI’s Grok, the implications of recent breakthroughs in AI reasoning, the rise of short-form video generation AI in social media and advertising, the challenges Europe faces in keeping pace with the US and China in AI innovation and much more.Links Mentioned in the Show:Data & AI Trends & Predictions 2025Skill Track: AI Business FundamentalsRelated Episode: Reviewing Our Data Trends & Predictions of 2024 with DataCamp's CEO & COO, Jonathan Cornelissen & Martijn TheuwissenRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

2024 was another huge year for data and AI. Generative AI continued to shape the way we work and interact with technology, with companies of all sizes racing to integrate AI into their products. We saw strides in tools like AI-enhanced data science notebooks, rapid adoption of generative image AI, and a steady march toward video generation AI. At the same time, foundational skills like AI literacy and data governance gained traction as critical areas for individuals and organizations to master.This time last year, DataCamp Co-Founders Jonathan and Martijn made a series of predictions and data and AI for 2024, today, they join Richie to reflect on their 2024 predictions and share their vision for data and AI in 2025.In the episode, Richie, Jonathan, and Martijn review the mainstream adoption of generative AI and its journey toward daily use, the rise of AI literacy as a critical skill, the growing overlap between data science and software engineering with the emergence of AI engineers, evolving trends in programming languages, how generative AI has moved from prototype to production, the near-mainstreaming of video generation AI, why AI hype continues to thrive and much more.Links Mentioned in the Show:Data & AI Trends & Predictions 2025Skill Track: AI Business FundamentalsRelated Episode: Data Trends & Predictions 2024 with DataCamp's CEO & COO, Jonathan Cornelissen & Martijn TheuwissenRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

AI is not just about writing code; it's about improving the entire software development process. From generating documentation to automating code reviews, AI tools are becoming indispensable. But how do you ensure the quality of AI-generated code? What strategies can you employ to maintain high standards while leveraging AI's capabilities? These are the questions developers must consider as they incorporate AI into their workflows.Eran Yahav is an associate professor at the Computer Science Department at the Technion – Israel Institute of Technology and co-founder and CTO of Tabnine (formerly Codota). Prior to that, he was a research staff member at the IBM T.J. Watson Research Center in New York (2004-2010). He received his Ph.D. from Tel Aviv University (2005) and his B.Sc. from the Technion in 1996. His research interests include program analysis, program synthesis, and program verification. Eran is a recipient of the prestigious Alon Fellowship for Outstanding Young Researchers, the Andre Deloro Career Advancement Chair in Engineering, the 2020 Robin Milner Young Researcher Award (POPL talk here), the ERC Consolidator Grant as well as multiple best paper awards at various conferences.In the episode, Richie and Eran explore AI's role in software development, the balance between AI assistance and manual coding, the impact of generative AI on code review and documentation, the evolution of developer tools, and the future of AI-driven workflows, and much more.Links Mentioned in the Show:TabnineConnect with EranCourse: Working with the OpenAI APIRelated Episode: Getting Generative AI Into Production with Lin Qiao, CEO and Co-Founder of Fireworks AIRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

AI features and products are the hottest area of software development. Creating high quality AI software is both essential and challenging for many businesses. In this episode, we look at retrieval augmented generation, an important technique for improving text generation quality in AI applications. Beyond technical measures, we look at the broader quality problem for AI applications. How do you ensure your AI applications are effective and secure? What steps should you take to integrate AI into your existing data governance frameworks? And how do you measure the success of these AI-driven solutions?Theresa Parker is the Director of Product Management at Rocket Software. She has 25 years of experience as a technology executive with a focus on software development processes, consultancy, and business development. Her recent work in content management focuses on the use of AI and RAG to improve content discoverability.Sudhi Balan is the Chief Technology Officer for AI & Cloud. He leads the AI and data teams for data modernization, driving AI adoption of Rocket's structured and unstructured data products. He also shapes AI strategy for Rocket’s infrastructure and app portfolio. He has earned patents for safe and scalable applications of transformational technology. Previously, he led digital transformation and hybrid cloud strategy for Rocket’s unstructured data business and was Senior Director of Product Development at ASG.In the episode, Richie, Theresa, and Sudhi explore retrieval-augmented generation, its applications in customer support and loan processing, the importance of data governance and privacy, the role of testing and guardrails in AI, cost management strategies, and the potential of AI to transform customer experiences, and much more.Links Mentioned in the Show:Rocket SoftwareConnect with Theresa and SudhiCourse: Retrieval Augmented Generation (RAG) with LangChainRelated Episode: Getting Generative AI Into Production with Lin Qiao, CEO and Co-Founder of Fireworks AIRewatch sessions from RADAR: Forward EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As we look back at 2024, we're highlighting some of our favourite episodes of the year, and with 100 of them to choose from, it wasn't easy!The four guests we'll be recapping with are:Lea Pica - A celebrity in the data storytelling and visualisation space. Richie and Lea cover the full picture of data presentation, how to understand your audience, how to leverage hollywood storytelling and more. Out December 19.Alex Banks - Founder of Sunday Signal. Adel and Alex cover Alex’s journey into AI and what led him to create Sunday Signal, the potential of AI, prompt engineering at its most basic level, chain of thought prompting, the future of LLMs and more. Out December 23.Don Chamberlin - The renowned co-inventor of SQL. Richie and Don explore the early development of SQL, how it became standardized, the future of SQL through NoSQL and SQL++ and more. Out December 26.Tom Tunguz - general Partner at Theory Ventures, a $235m VC firm. Richie and Tom explore trends in generative AI, cloud+local hybrid workflows, data security, the future of business intelligence and data analytics, AI in the corporate sector and more. Out December 30.Rapid change seems to be the new norm within the data and AI space, and due to the ecosystem constantly changing, it can be tricky to keep up. Fortunately, any self-respecting venture capitalist looking into data and AI will stay on top of what’s changing and where the next big breakthroughs are likely to come from. We all want to know which important trends are emerging and how we can take advantage of them, so why not learn from a leading VC. Tomasz Tunguz is a General Partner at Theory Ventures, a $235m early-stage venture capital firm. He blogs sat tomtunguz.com & co-authored Winning with Data. He has worked or works with Looker, Kustomer, Monte Carlo, Dremio, Omni, Hex, Spot, Arbitrum, Sui & many others.He was previously the product manager for Google's social media monetization team, including the Google-MySpace partnership, and managed the launches of AdSense into six new markets in Europe and Asia. Before Google, Tunguz developed systems for the Department of Homeland Security at Appian Corporation. In the episode, Richie and Tom explore trends in generative AI, the impact of AI on professional fields, cloud+local hybrid workflows, data security, and changes in data warehousing through the use of integrated AI tools, the future of business intelligence and data analytics, the challenges and opportunities surrounding AI in the corporate sector. You'll also get to discover Tom's picks for the hottest new data startups.Links Mentioned in the Show:Tom’s BlogTheory VenturesArticle: What Air Canada Lost In ‘Remarkable’ Lying AI Chatbot Case[Course] Implementing AI Solutions in BusinessRelated Episode: Making Better Decisions using Data & AI with Cassie Kozyrkov, Google's First Chief Decision ScientistSign up to RADAR: AI EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As we look back at 2024, we're highlighting some of our favourite episodes of the year, and with 100 of them to choose from, it wasn't easy!The four guests we'll be recapping with are:Lea Pica - A celebrity in the data storytelling and visualisation space. Richie and Lea cover the full picture of data presentation, how to understand your audience, how to leverage hollywood storytelling and more. Out December 19.Alex Banks - Founder of Sunday Signal. Adel and Alex cover Alex’s journey into AI and what led him to create Sunday Signal, the potential of AI, prompt engineering at its most basic level, chain of thought prompting, the future of LLMs and more. Out December 23.Don Chamberlin - The renowned co-inventor of SQL. Richie and Don explore the early development of SQL, how it became standardized, the future of SQL through NoSQL and SQL++ and more. Out December 26.Tom Tunguz - general Partner at Theory Ventures, a $235m VC firm. Richie and Tom explore trends in generative AI, cloud+local hybrid workflows, data security, the future of business intelligence and data analytics, AI in the corporate sector and more. Out December 30.For our 200th episode, we bring you a special guest and taking a walk down memory lane—to the creation and development of one of the most popular programming languages in the world.Don Chamberlin is renowned as the co-inventor of SQL (Structured Query Language), the predominant database language globally, which he developed with Raymond Boyce in the mid-1970s. Chamberlin's professional career began at IBM Research in Yorktown Heights, New York, following a summer internship there during his academic years. His work on IBM's System R project led to the first SQL implementation and significantly advanced IBM’s relational database technology. His contributions were recognized when he was made an IBM Fellow in 2003 and later a Fellow of the Computer History Museum in 2009 for his pioneering work on SQL and database architectures. Chamberlin also contributed to the development of XQuery, an XML query language, as part of the W3C, which became a W3C Recommendation in January 2007. Additionally, he holds fellowships with ACM and IEEE and is a member of the National Academy of Engineering.In the episode, Richie and Don explore his early career at IBM and the development of his interest in databases alongside Ray Boyce, the database task group (DBTG), the transition to relational databases and the early development of SQL, the commercialization and adoption of SQL, how it became standardized, how it evolved and spread via open source, the future of SQL through NoSQL and SQL++ and much more. Links Mentioned in the Show:The first-ever journal paper on SQL. SEQUEL: A Structured English Query LanguageDon’s Book: SQL++ for SQL Users: A TutorialSystem R: Relational approach to database managementSQL CoursesSQL Articles, Tutorials and Code-AlongsRelated Episode: Scaling Enterprise Analytics with Libby Duane Adams, Chief Advocacy Officer and Co-Founder of AlteryxRewatch sessions from RADAR: The Analytics EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As we look back at 2024, we're highlighting some of our favourite episodes of the year, and with 100 of them to choose from, it wasn't easy!The four guests we'll be recapping with are:Lea Pica - A celebrity in the data storytelling and visualisation space. Richie and Lea cover the full picture of data presentation, how to understand your audience, how to leverage hollywood storytelling and more. Out December 19.Alex Banks - Founder of Sunday Signal. Adel and Alex cover Alex’s journey into AI and what led him to create Sunday Signal, the potential of AI, prompt engineering at its most basic level, chain of thought prompting, the future of LLMs and more. Out December 23.Don Chamberlin - The renowned co-inventor of SQL. Richie and Don explore the early development of SQL, how it became standardized, the future of SQL through NoSQL and SQL++ and more. Out December 26.Tom Tunguz - general Partner at Theory Ventures, a $235m VC firm. Richie and Tom explore trends in generative AI, cloud+local hybrid workflows, data security, the future of business intelligence and data analytics, AI in the corporate sector and more. Out December 30.Since the launch of ChatGPT, one of the trending terms outside of ChatGPT itself has been prompt engineering. This act of carefully crafting your instructions is treated as alchemy by some and science by others. So what makes an effective prompt?Alex Banks has been building and scaling AI products since 2021. He writes Sunday Signal, a newsletter offering a blend of AI advancements and broader thought-provoking insights. His expertise extends to social media platforms on X/Twitter and LinkedIn, where he educates a diverse audience on leveraging AI to enhance productivity and transform daily life.In the episode, Alex and Adel cover Alex’s journey into AI and what led him to create Sunday Signal, the potential of AI, prompt engineering at its most basic level, strategies for better prompting, chain of thought prompting, prompt engineering as a skill and career path, building your own AI tools rather than using consumer AI products, AI literacy, the future of LLMs and much more. Links Mentioned in the Show:[Alex’s Free Course on DataCamp] Understanding Prompt EngineeringSunday SignalPrinciples by Ray Dalio: Life and WorkRelated Episode: [DataFramed AI Series #1] ChatGPT and the OpenAI Developer EcosystemRewatch sessions from RADAR: The Analytics EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

As we look back at 2024, we're highlighting some of our favourite episodes of the year, and with 100 of them to choose from, it wasn't easy!The four guests we'll be recapping with are:Lea Pica - A celebrity in the data storytelling and visualisation space. Richie and Lea cover the full picture of data presentation, how to understand your audience, how to leverage hollywood storytelling and more. Out December 19.Alex Banks - Founder of Sunday Signal. Adel and Alex cover Alex’s journey into AI and what led him to create Sunday Signal, the potential of AI, prompt engineering at its most basic level, chain of thought prompting, the future of LLMs and more. Out December 23.Don Chamberlin - The renowned co-inventor of SQL. Richie and Don explore the early development of SQL, how it became standardized, the future of SQL through NoSQL and SQL++ and more. Out December 26.Tom Tunguz - general Partner at Theory Ventures, a $235m VC firm. Richie and Tom explore trends in generative AI, cloud+local hybrid workflows, data security, the future of business intelligence and data analytics, AI in the corporate sector and more. Out December 30.Your data project doesn't end once you have results. In order to have impact, you need to communicate those results to others. Presentations filled with endless tables and technical jargon can easily become tedious, leading your audience to lose interest or misunderstand your point.Data storytelling provides a solution to this: by creating a narrative around your results you can increase engagement and understanding from your audience. This is an art, and there are so many factors that contribute to visualizing data and creating a compelling story, it can be overwhelming. However, with the right approach, creating data stories can become second nature. In this special episode of DataFramed, we join forces with the Present Beyond Measure podcast to glean the best data presentation practices from one of the leading voices in the space.Lea Pica host of the Founder and Host of the Present Beyond Measure podcast and is a seasoned digital analytics practitioner, social media marketer and blogger with over 11 years of experience building search marketing and digital analytics practices for companies like Scholastic, Victoria’s Secret and Prudential.Present Beyond Measure’s mission is to bring their teachings to the digital marketing and web analytics communities, and empower anyone responsible for presenting data to an audience.In the full episode, Richie and Lea cover the full picture of data presentation, how to understand your audience, leverage hollywood storytelling, data storyboarding and visualization, the use of imagery in presentations, cognitive load management, the use of throughlines in presentations, how to improve your speaking and engagement skills, data visualization techniques in business setting and much more. Links Mentioned in the Show:Present Beyond MeasureLea’s BookConnect with Lea on LinkedinHollywood Storytelling[Course] Data Storytelling ConceptsNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business