Defining Data Analytics, Machine Learning, and Data Science

Other Ways to Listen: bit.ly/listen-dbp

Data analytics, machine learning, and data science—those are the three things that this podcast focuses its discussions on. This episode provides my definitions in descending order of their complexity in terms of the depth of required knowledge, competencies, and practical, demonstrable skills related to computer science and programming, mathematics and statistics, critical thinking and overall approach to solving problems with data.

My definitions also reflect a descending order of analytical advancement, because I see data science as advanced machine learning, and machine learning as advanced data analytics.

Here’s a curated list of recommended resources offering other perspectives:

• What on earth is data science? — Blog post by Cassie Kozyrkov, which includes links to related posts on Statistics, Machine Learning, Data-mining / Analytics.

• Making Friends with Machine Learning — YouTube Playlist by Cassie Kozyrkov of what was an internal-only (now available to everyone) Google course created to inspire beginners and amuse experts.  

This episode was sponsored by Vertica, the unified analytics platform based on a massively scalable architecture with the broadest set of analytical functions spanning event and time series, pattern matching, geospatial, and end-to-end in-database machine learning.

Learn More at https://www.vertica.com/