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7/20 Meet-Up: Model Deployment with Bob Grossman

Garrett Long July 26, 2016
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Last Wednesday, Open Data Group had the opportunity to co-host a data science meet-up with DataScope, which manages the Data Science Chicago Meet-Up. We thoroughly enjoyed the experience and appreciate all the folks who came out for discussion and pizza. Bob Grossman, Open Data’s founder and Chief Data Scientist, introduced the concept of AnalyticOps (read CTO Stu Bailey’s posts on the same topic here) and the emerging core competency of deploying models. Bob was joined by Robert Nendorf from Allstate, who shared his views on a similar topic: DevOps for Data Science.

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AnalyticOps: Part 4 - What is AnalyticOps?

Garrett Long June 8, 2016
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How is AnalyticOps different than DevOps or Data Science?

Well, it took four parts to get to this point, but we’ve used our time to discuss some of the abstractions that are required to understand the idea referred to as “AnalyticOps”. Our journey started with the abstract concept of “what is an analytic” while the second covered the operative concept of “deploying” the analytic with an analytic engine or deployment server.  

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AnalyticOps: Part 3 - What is an Analytic Engine?

Garrett Long May 25, 2016
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How are Analytic Engines different than “deployment servers”?

Well, did you do last week's homework? If you used the emerging analytic standards of PFA or PPFA to create an analytic for trajectory planning, please send it to info@opendatagroup.com. You just might get a job offer! Heck, if you use the open source tools Aurelius or Titus to convert your R or Python models to PFA we’d love to hear it, and share your work with the growing community of analytic engine users.

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AnalyticOps: Part 2 - What is an Analytic Anyway? cont.

Garrett Long May 19, 2016
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or Is an “analytic” just a fancy term for a “business rule”? 

On Monday, I outlined my view of what makes “an analytic” and the jargon that goes along with it. I ended the post wondering whether “an analytic” is just another name for “business rules” that organizations tend to follow today. In my view, the main difference between the two, which might be no difference at all for a given situation, is that "analytics" are generally more complex mathematically and operate on a more general "feature space". This generalization allows rigorously developed techniques from statistics and applied mathematics to have a chance at being applied to a messy real world problem. 

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AnalyticOps: Part 1 - What is an Analytic Anyway?

Garrett Long May 16, 2016
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Or is an “analytic” just a fancy term for a “business rule”? 

Over the next few blog posts, I am going to tackle the subject of AnalyticOps, a relatively new function that organizations are going to have to implement and master to ensure maximum ROI on data science investments.  I’ll start with some basics of defining just what is “an analytic” and move through some key elements of implementing the tools (an Analytic Engine) and the competencies that make up AnalyticOps.

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