Building Data Science Teams

I delivered a session called “Building Data Science Teams” (viewable on YouTube) at EMC World. As I mentioned during the presentation, as much as the media is focusing on the shortage of Data Scientists, the reality is that to do it well, you must consider data science as a team sport. The success of a project is not just on the shoulders of Data Scientists; it also requires a number of other roles within a team, such as Data Engineers, BI Analysts, and strong stakeholders. See the image below for an overview of the seven roles that are common in these projects:

In addition to a shortage of Data Scientists, we are also experiencing a shortage of data savvy managers. These are the people who understand how to make better decisions with data, and who also work with their teams to design insightful ways to use data to test ideas.

In my talk at EMC World, I talked about many of the elements that people need to consider as they build data science teams and architect this capability within an organization.  My session focused on these 4 main areas:

• Data Science Team.  The roles and competencies required for a high-performing data science team.

1. Developing Data Science Capabilities.  Deciding which model to choose for developing data science capabilities, because not everyone needs to build their own team. In other words, you should consider whether it is best to transform an existing team, build a brand new one, outsource, or crowdsource specific data science problems.
2. Organizational Model.  Organizations may choose to have a centralized data science team, a de-centralized one, or take a hybrid approach.  The key is to understand the trade-offs of each path and be thoughtful in the path you pursue.
3. Executive Engagement.  Getting executive engagement and support is critical.  This is what separates a company with localized analytical teams from another that uses analytics to really inform its strategy. Think of Netflix, Amazon, or the Oakland A’s (Moneyball) in this latter category.

During EMC World, I also did a short presentation in the EMC Global Services Booth that focused on implementing Big Data projects and the shortage of people with the necessary data science skills. You can watch a short video from my presentation in which I break down the key roles that are needed as part of a data science team and the skills that are necessary at each level.

Much of the content for these sessions was taken from the data science and Big Data analytics courses that I helped develop at EMC. The newest course, designed specifically for business leaders, Data Science and Big Data Analytics for Business Transformation, is offered as a free, 90 minute executive module, as well as a more comprehensive one-day class on DVD.  For those wishing to develop greater skills as a data science practitioner, Data Science and Big Data Analytics is a five-day course offered via DVD or in classroom.

The initial feedback from these courses has been very positive. I’ve received emails from Directors of Analytics at companies who have attended the class or watched it on video, and feel it was on the mark and important to train people on these topics.  I expect as more organizations figure out that Big Data is critical to their future success, they will tap more of their leaders to get trained so they can make an impact with Big Data.