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Scott Burk

Austin, United States

Founder, It’s All Analytics (
Scott Burk is an author of four books on AI, data science and analytics including the It’s All Analytics Series, the Executive Guide for AI and Analytics and Practical Data Analytics for Innovation in Medicine. He currently teaches in the Master of Data Science program at CUNY and has taught at Baylor and Texas A&M. He has worked for startups in multiple industries as well as established firms like Texas Instruments, Dell, Paypal, EBay, and in healthcare. Scott has a bachelors in biology and chemistry, master degrees in finance, statistics and data mining and a PhD in statistics. Scott has a data science consulting practice and resides in Central Texas

His experience is primarily in application, solving difficult analytical problems. He as a divers experience that includes a variety of executive (VP and Director) level positions in finance, IT, statistics, engineering, sales and marketing as well as front line, technical positions. Data has been the thread that has tied his professional experience together.

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Travels From: Austin, Texas
Speaking Topics: AI, Data Infrastructure for Data Science, Analytics

Scott Burk Points
Academic 0
Author 60
Influencer 55
Speaker 0
Entrepreneur 0
Total 115

Points based upon Thinkers360 patent-pending algorithm.

Thought Leader Profile

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Areas of Expertise

AI 30.83
Analytics 34.99
Predictive Analytics 30.83

Industry Experience


1 Book
It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690)
Francis and Taylor, CRC Press
July 09, 2020
Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, "analytics," is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology?

This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series.

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Tags: AI, Analytics, Predictive Analytics



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Scott Burk