Weekly Round-Up: Data Science Metro Map, Big Data Workers, Prescriptive Analytics, and Knewton

Welcome back to the round-up, an overview of the most interesting data science, statistics, and analytics articles of the past week. This week, we have 4 fascinating articles ranging in topics from big data workers to educational recommendation algorithms. In this week's round-up:

  • Becoming a Data Scientist – Curriculum via Metromap
  • The Growing Need for Big Data Workers: Meeting the Challenge With Training
  • How Prescriptive Analytics Could Harness Big Data to See the Future
  • Q&A With Knewton’s David Kuntz, Maker of Algorithms

Becoming a Data Scientist – Curriculum via Metromap

For those of you looking to get started learning data science but don't know where to begin, this blog post literally maps it out for you. The author has taken the broad subject of data science and created a train map similar to those found in all major cities with public transportation. The different tracks of data science are depicted as different color train lines in the map and the subjects within those tracks are depicted as stops along those lines. Very interesting and definitely worth a look!

The Growing Need for Big Data Workers: Meeting the Challenge With Training

This is a Wired article about how the need for big data workers is growing as there is more and more data that needs to be collected, organized, analyzed, and acted upon. The article talks about the challenges of educating people and highlights the efforts of a few companies such as IBM, Big Data University, and DeveloperWorks.

Speaking of data science education, Data Community DC is hosting a Natural Language Processing Basics workshop on July 27th and there are still a few seats left. You can view details and sign up here.

How Prescriptive Analytics Could Harness Big Data to See the Future

Our third piece this week is about prescriptive analytics and how organizations can use it to help them make data-driven improvements in their operations. The article defines prescriptive analytics, contrasts it with the more commonly used descriptive and predictive analytics, and provides some examples as to how it can be useful.

Q&A With Knewton’s David Kuntz, Maker of Algorithms

Our final piece this week is an article about a company call Knewton and the interesting work they do. Knewton designs recommendation systems for educational products, which help customize the learning experience and tailor it to the individual student. In this article the author interviews David Kuntz, who is Knewton's Vice President of Research, about how their technology works, what kinds of things it can do, and what this means for education in the future.

That's it for this week. Make sure to come back next week when we’ll have some more interesting articles! If there's something we missed, feel free to let us know in the comments below.

Read Our Other Round-Ups