Weekly Round-Up: Data Science Roles, Technology Stacks, Predictive Analytics, and Michael Jordan

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 data science technology stacks to Michael Jordan. In this week's round-up:

  • Five Roles You Need on Your Big Data Team
  • Choosing a Data Science Technology Stack
  • 12 Predictive Analytics Screw-ups
  • What Michael Jordan Can Teach Us About Big Data, Strategy And Innovation

Five Roles You Need on Your Big Data Team

Our first piece this week is an HBR article about the different roles you need when building a data science team. Data science is a very broad field and because of this, it's difficult to find someone who has all the skills that fall under its umbrella. This article attempts to break down the skill sets into more specific roles that can work together to really create value for an organization. The article lists the different roles, describes them, and also talks about the kind of culture you need to develop in order to get everyone in the organization on board and on the same page.

Choosing a Data Science Technology Stack

This is an interesting blog post about different data science technology stacks and how we as data scientists go about choosing one that works best for us. The author points out that there are several layers to a data science stack - sourcing the data, storing it, exploring it, modeling it, etc. - and there are several technological options available for performing each layer. The post examines these different options and even has a survey you can enter the technologies you use for each layer. When the survey is complete, those who participated will be emailed the results.

12 Predictive Analytics Screw-ups

This is a ComputerWorld article about some of the pitfalls you would do well to avoid when performing predictive analytics. The author interviewed experts at 3 data science consulting firms - Elder Research, Abbott Analytics, and Prediction Impact - about about the different mistakes they encounter to come up with this list. Take a look through them and see how many you've encountered yourself!

What Michael Jordan Can Teach Us About Big Data, Strategy And Innovation

Our final piece this week is a Forbes article that uses Michael Jordan and other sports examples to drive home points about big data and how we use it in business. The author starts out by drawing a parallel between the types of decisions managers need to make these days about new technologies, opportunities, and employees to looking at Michael in his early days when his athletic potential wasn't as obvious. He continues through the rest of the article writing about the processes we go through, the data we look at in our attempts to evaluate a situation and make appropriate decisions, and how big data and advances in technology improve our abilities to do all these things over time.

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