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Paul Bremner
  • San Jose, California
  • United States
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Latest Activity

Paul Bremner commented on William Vorhies's blog post 6 Predictions about Data Science, Machine Learning, and AI for 2018
"Bill, Great observations with very interesting implications for data science/scientists.   I recently started SAS’s Enterprise Miner course and was blown away by the speed Data Science Platforms (DSPs) provide in cleaning data,…"
yesterday
Paul Bremner liked William Vorhies's blog post 6 Predictions about Data Science, Machine Learning, and AI for 2018
Thursday
Paul Bremner commented on William Vorhies's blog post Machine Learning – Can We Please Just Agree What This Means
"I still struggle with what people really mean by "Big Data", particularly people using R.  The Revolution Analytics folks (acquired by Microsoft) typically mean massive quantities of structured data and the need for Revoscale R to get…"
Dec 7
Paul Bremner replied to DOUG T AMLIN's discussion Been in Analytics for 3 yrs- need to know where to REALLY start!
"One approach is to see what's being used in the "Big Data" jobs at your firm.  Looks like you're in pricing now and I'm not sure how much unstructured data (if that's how you're defining "big data")…"
Oct 31

Profile Information

Short Bio
Former CIA Analyst (15 years, about 2/3 working on Russian military, then following international telecom/computer industry and supporting trade negotiators), worked on Market Intelligence at IBM, AT&T, Pacific Northwest National Laboratory (Department of Energy R&D lab), Cisco. Transitioning into Marketing/Business Analytics using SAS and SQL, probably adding Python or R at some point.

[email protected]
My Web Site Or LinkedIn Profile
http://www.linkedin.com/in/paulmbremner/
Field of Expertise
Analytics, Data Integration, Visualization, BI, Data Science
Professional Status
Manager
Your Job Title:
Marketing Intelligence and Analytics Manager
Interests:
Finding a new position, Networking

Paul Bremner's Blog

Comment on "Why R is Bad for You"

Posted on May 25, 2017 at 8:30am 1 Comment

There seems to be a lot confusion about the role of programming in relation to the Data Science platforms that research firms Gartner and Forrester have identified as the future of Data Science in large corporations.  For example, numerous people have stated that SAS is pushing a drag-and-drop platform (Enterprise Miner) that somehow limits choices and is destined to fail due to the fact that using programming (that is, R) allows greater flexibility.

It’s certainly…

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