My new job title at Enterprise Data & Analytics is Chief Data Engineer.

“What’s a Data Engineer, Andy?”

I’m glad you asked! Data Science is a broad term applied to analytics derived from the statistical analysis of data. “So, what do data scientists actually do?” That’s a fantastic question: Data scientists experiment. they use tools like R and D3, languages like Python, and platforms like Azure Machine Learning to tinker with weights applied to data measures. Then they observe the results. It’s, well, science.

Before data science can happen, though, the data used by Data Scientists must be collected, cleansed (because garbage in still equals garbage out), coalesced into consistent units of measure, and formatted for consumption by the analytical engine. This part of the job is called data wrangling, munging, or data integration; and it’s 50-90% of the work!

This is data engineering.*

It’s All About Me

I’ve been doing data integration since before I knew what it was called. I cannot tell you what drew me to this type of work, but I can also not deny I was drawn to it. I seemed to have a knack (as we say in Farmville Virginia…) for it. I enjoyed it. It was useful work. And, for some unknown reason, I was good at it.

So I changed my title at Enterprise Data & Analytics to better reflect this reality.

More to Come

This isn’t the only change we’re making at Enterprise Data & Analytics. As we continue to grow, we are making other changes that will be announced soon. I cannot wait to share with you the cool stuff we’re working on right now! But, I must refrain. For now. More later!

:{>

* I found a couple good articles on the difference between Data Science and Data Engineering:
Data Science vs. Data Engineering
What is Data Engineering