Demystifying Data Science

OCDQ Radio is a vendor-neutral podcast about data quality and its related disciplines, produced and hosted by Jim Harris.

During this episode, special guest, and actual data scientist, Dr. Melinda Thielbar, a Ph.D. Statistician, and I attempt to demystify data science by explaining what a data scientist does, including the requisite skills involved, bridging the communication gap between data scientists and business leaders, delivering data products business users can use on their own, and providing a straightforward explanation of key concepts such as signal-to-noise ratio, uncertainty, experimentation, and correlation.

Melinda Thielbar is the Senior Mathematician for IAVO Research and Scientific.  Her work there focuses on power system optimization using real-time prediction models.  She has worked as a software developer, an analytic lead for big data implementations, and a statistics and programming teacher.

Melinda Thielbar is a co-founder of Research Triangle Analysts, a professional group for analysts and data scientists located in the Research Triangle of North Carolina.

While Melinda Thielbar doesn’t specialize in a single field, she is particularly interested in power systems because, as she puts it, “A power systems optimizer has to work every time.”

 

Demystifying Data Science

Additional listening options:

 

Related OCDQ Radio Episodes

Clicking on the link will take you to the episode’s blog post:

  • Data Quality and Big Data — Guest Tom Redman (aka the “Data Doc”) discusses Data Quality and Big Data, including if data quality matters less in larger data sets, and if statistical outliers represent business insights or data quality issues.

 

Related Posts

There is No Such Thing as a Root Cause

Big Data and the Infinite Inbox

HoardaBytes and the Big Data Lebowski

OCDQ Radio - Data Quality and Big Data

Will Big Data be Blinded by Data Science?

Magic Elephants, Data Psychics, and Invisible Gorillas

The Graystone Effects of Big Data

Information Overload Revisited

Exercise Better Data Management

A Tale of Two Datas

How Predictable Are You?

A Statistically Significant Resolution for 2013

What Magic Tricks teach us about Data Science

What Mozart for Babies teaches us about Data Science

It’s Not about being Data-Driven

Big Data, Sporks, and Decision Frames

Big Data: Structure and Quality

Darth Vader, Big Data, and Predictive Analytics

Big Data, Predictive Analytics, and the Ideal Chronicler

The Big Data Theory