Why you need a data strategy, and what happens if you don’t have one
How to map out a plan for finding value in data.
Jerry Overton
Jerry Overton is a Data Scientist and Distinguished Technologist in DXC’s Analytics group. He is the Principal Data Scientist for the strategic alliance between DXC and Microsoft known as Industrial Machine Learning—enterprise-scale applications across six different industries: banking and capital markets, energy and technology, insurance, manufacturing, healthcare, and retail.
Jerry is the author of the O'Reilly Media eBook Going Pro in Data Science: What It Takes to Succeed as a Professional Data Scientist. He teaches the Safari live online training course Mastering Data Science at Enterprise Scale: How to design and implement machine-learning solutions that improve your organization. In his blog, Doing Data Science, Jerry shares his experiences leading open research and transforming organizations using data science.
Radar
There’s nothing magical about learning data science
The top 5 habits of a professional data scientist.
How to think like a data scientist
Using induction to test your hypotheses
What to look for in a data scientist
How an algorithm is to a data scientist what a compound microscope is to a biologist.
Content
A lesson in prescriptive modeling
Simulate new business models and practices with open source code.
Going pro in data science
In this report, you will learn practices for making good decisions with missing or sketchy information, and advice for surviving (and even thriving) as a data scientist in your organization.
What it means to “go pro” in data science
A look at what it takes to be a professional data science programmer.
The key to agile data science: experimentation
A real-world example of how a short delivery cycle fosters creativity.