Data Driven

Varigance is poised to release the 2018 version of their toolset: BimlExpress, BimlStudio, and BimlFlex. BimlHero Andy Leonard has an update!

Frank and Andy are in the same place for the first time in a while and they have a special announcement: the show has reached 50,000 downloads in just under one year. Thank you for supporting the show. You rock!

Frank caught up with Karen Lopez at the Philly Azure Data Fest to talk rocket science, data, and the perils of developers misusing columns in the schema. We also uncover the meaning of DBA (Don’t Bother Asking) and a super secret flag to make your databases run faster. (Not really)

At the Philly Azure Data Fest, Frank sits down with Tim McAliley to find out where Azure Data Fest started and where it’s headed to next,

Frank and Andy are out and about and if they can’t be in the studio, they are going to bring the studio to where they are in order to keep you up to date on all the data happenings out there. In this Data Point, Frank is at the Philadephia Azure Data Fest to listen, learn, and record. He also talks about the recent announcements from the Microsoft Build conference earlier this week.

… and Andy’s delivering training! From Frank and Andy at Data Driven: “For those about to teach, WE SALUTE YOU!” Happy Teacher Appreciation Day, teachers! You rock! :{>

Andy ran into Kathi Kellenberger at SQL Saturday Albuquerque to talk about her career change, Breaking Bad, and loving your job.

Andy ran into Jason Brimhall, certified Data Master, about high volume transactions, big data, and how DBAs fit into the Data Science picture.

Andy speaks with Meagan Longoria about the importance of creating accessible reports in PowerBI, SQL Pass and more.

Andy may not be the one who knocks, but he is in Albuquerque for SQL Saturday. He runs into DBA extraordinaire as to how DBAs fit into the Data Science ecosystem and why they say no to developers so often. via GIPHY

With Andy travelling around and Frank starting a new job, Frank and Andy have not had a lot of studio time lately. So, they are bringing the studio to you by creating more Data Point shows, which bring you some of the brightest minds they run into out in “the wilds of Data Science” as well as their thoughts and insights on the spot wherever they go. Where possible, Frank uses his ninja editing skills to filter out background noise and make the listening experience as pleasurable as it is educational.

A few years ago, Andy collected local weather data from his farm near Farmville Virginia and posted it online. Why? To see if he could. Even though the old weather station ceased working years ago, he still uses the data in SSIS training courses he delivers. It was time for a new weather station, so Andy picked up this Acurite model. He plans to use it to conduct data science and data engineering experiments. Why? To see if he could. To get things started, Andy set up the Acurite software to append readings to a CSV file every 12 minutes. He then grabbed a copy of the AzCopy command-line utility Andy decided to run the Acurite software and AzCopy on a very old Windows 7 machine (with only 2GB RAM). Why? To see if he could. It works. Andy built a command line for AzCopy that performs a data transfer from the old Win7 machine to Azure Blob Storage. He then used Task Scheduler to fire the command line every 15 minutes… and you already know why. :{>

In this DataPoint, Frank talks about the term “Data Estate” in front of an actual estate.

Andy is suffering from seasonal allergies but the allergy meter says pollen is low. What gives? Outliers. That’s what. Here’s the bar chart to which Andy refers: Here’s a pollen heat map:

After attending the Global Azure Bootcamp with my son, I decided to drop in and see what bargains there were at the nearby Toys R Us. I have fond memories of going to Toys R Us when I was a kid. However, I’ve noticed a distinct decline in the store over the last few years. Given the state of their business, I know I am not the only one to see this once great retailer fall from grace. It was a weird feeling walking through a store I had fond memories of and picking through its carcass like a vulture feasting on roadkill. Naturally, the pundits will point the blame of Toys R Us at Amazon, but is that fair? Is it accurate? Well, kind of. Jeff Bezos recently talked about his “one character” emails that forwards to his senior managers when he fields a complaint from the public. These emails not only strike fear into the hearts of the most senior executives at the online retailer, they also spur these leaders to act immediately to resolve the customer issues. What killed Toys R Us wasn’t Amazon: it was Amazon’s relentless commitment to customer service against large retailers who’ve grown lazy and content. Now that consumers have a choice, they will choose to do business with those companies that provide the best customer experience. Ok, But How Does Data Fit into this? It does indirectly. From the article: [emphasis added] So those customer complaints gives him front-line insights. If all of his data say one thing and a few customers say something else, he believes the customers. “The thing I have noticed is when the anecdotes and the data disagree, the anecdotes are usually right. There’s something wrong with the way you are measuring it,” he explained. Naturally, as a data professional, those two phrases caught my attention. In fact, I see this as a failing in more than one enterprise: the assumption that the BI dashboard knows all. It might, but it very well may not. If the data tells a different story from what’s going on in the field, then is the field wrong or is the data incomplete? Put another way: If the map says that there’s a road and there is no road, is the map wrong or is reality wrong? Clearly, reality is the ultimate arbiter and if you’re business is retail, then your reality is customer perception, not what the pretty graphics on your KPIs say.

In this DataPoint, Frank talk to Brian Moran about Global Azure Bootcamp, Databricks, AI, and life at Microsoft. As this is Mr. Moran’s third appearance, this makes him Data Driven’s first ever threepeat guest.  

Recently, I delivered a presentation on “Data Science for the Curious” at the WeWork K Street location in Washington, DC. The goal was to help the largely non-technical audience of public policy professionals understand some of the core tenets of data science: its promises and its perils. In light of the recent Facebook revelations, this is more critical now than ever before.

Frank ponders weather prediction models, the confusion matrix, and cognitive biases.

While at SQL Saturday Chicago, Andy gets recursive by talking to Andy. Seriously, he meets up with Andy Yun, one of the organizers of SQL Saturday Chicago.

Straight from the Windy City SQL Saturday, Andy chats with Cathrine Wilhelmsen to dicusss all things BIML, matching shirts, and data.

Andy’s in the Windy City on this St. Patrick’s Day attending SQL Saturday and he bumps into Bill Wolf.

In this Deep Dive, Frank and Andy delve into the depths of Data Integration and SQL Server Integration Service.

In this Data Point, Frank recounts how he has a new approach to troubleshooting WPF performance issues, or any issues for that matter.