Honest thinking about technology decisions. — Page 18

Data preparation is extremely important to your data analytics / big data projects. Good data preparation can lead to good data analytics outcomes.

Data Analytics means different things to different people. I discuss prescriptive vs descriptive analytics and try to explain why you should care.

So, what digital projects should you be chasing? Chase the ones that are focused on improving the customer experience

If you teams ask questions and dig into the data, you can be sure that you've do everything possible to minimize the possibilities of being "theranosed"

This is another capture of a cloudy sunrise over Myrtle Beach. This was captured with a Canon 5DSR and a Canon 16-35 f/4 sitting on a Gitzo 1228 MK2

A capture of a Burrowing Owl Couple checking things out from their hole.

Underdogs win all the time, which is why you should always continue to improve and become better than you were.

A quick capture of a mail bluebird at rest. He had spent most of the day trying to keep his new fledged babies safe and fed.

Good data science isn't about finding answers to questions. Good data science is about setting up your data and systems to allow you to find more questions.

This is a landscape photo of Mount Grinnell from a boat on Swiftcurrent Lake in Glacier National Park.

To second my review from 4 years ago...if you are looking for a headset and have multiple devices, get this Savi headset (I own the W745)

I spend a lot of time talking to companies about big data and data science. Many conversations are with people at the CxO level (CEO's, COO's, CFO's, etc

A meadow off of Camas Road in Glacier National Park.

This is another capture from our trip to Glacier. A few of the days we were there, the area was covered with either smoke or clouds, which made it

This is a Great Blue in Profile from a few years ago. Captured with Canon 7D and Canon 400mm 5.6 L