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Data Scientists: Grow and Sustain a Center of Excellence

May 21, 2012

Game-changing analytics applications don't spring spontaneously from bare earth. You must plant the seeds through continuing investments in applied data science and, of course, in the big data analytics platforms and tools that bring it all to fruition.

But you'll be tilling infertile soil if you don't invest in sustaining a data science center of excellence within your company. Applied data science is all about putting the people who drill the data in constant touch with those who understand the applications. In spite of the mythology surrounding geniuses who produce brilliance in splendid isolation, smart people really do need each other. Mutual stimulation and support are critical to the creative process, and science, in any form, is a restlessly creative exercise.

In establishing a center of excellence, you may go the formal or informal route.

The formal approach is to institute ongoing process for data-science collaboration, education, and information sharing. As such, the core function of your center of excellence might be to bridge heretofore siloed data-science disciplines that need to engage more effectively. The center of excellence's core objectives might include any or all of the following:

  • Multi-disciplinary cross-training: The program might focus on cross-training professionals from diverse data science disciplines--such as data mining, text analytics, and graph analysis--in key technical areas where their worlds are converging, such as big data, Hadoop, and machine learning.
  • Quant/suit alignment: The program might provide advanced analytics professionals with a forum where they can hook up with key data-savvy subject matter experts in diverse business functions.
  • Business analyst skills enhancement: The program might encourage business analysts to learn more sophisticated statistical techniques than their schooling instilled in them and more sophisticated tools than their spreadsheets.

The informal path is to encourage data scientists to engage with each other using whatever established collaboration tools, communities, and confabs your enterprise already has in place. This is the model under which centers of excellence coalesce organically from ongoing conversations.

For example, Friday lunch-and-learn sessions can be the informal nucleus of your center of excellence. To keep these from expiring through apathy, a core group of data scientists must commit to holding them regularly and refreshing them with compelling content. These events might serve any or all of the following functions in your data science initiatives:

  • Bonding: The events could be a key forum in which newly hired data scientists introduce themselves to their colleagues and show what they know.
  • Recruitment: The events could provide your data scientists with a collegial-style setting for grilling promising new talent who are interviewing for data-scientist positions.
  • Discovery: The events could be the primary educational resource for data scientists to discover the specialized knowledge that is scattered throughout their organization in such hot disciplines as MapReduce, R, machine learning, constraint-based optimization, natural language processing, behavioral analytics, sentiment monitoring, and social graph analysis. Or, at the very least, it might be a regular forum in which developers think outside their comfortable boxes and explore the diversity of other languages, models, and algorithms that are supported in their company's analytic sandboxing platform, such as Netezza Analytics.
  • Demonstration: The events could provide vendors with a forum for demonstrating new or forthcoming big data analytics solutions that everybody's buzzing about but few have seen in action. Your data scientists may want to use these sessions to demonstrate some new technology they've been playing with in the labs.

Creeping polarization, like general apathy, will kill your data science center of excellence if you don't watch out. Don't let the center of excellence, formal or informal, degenerate into warring camps of analytics professionals trying to hardsell their pet approaches as the one true religion.

Centers of excellence must serve as a bridge, not a barrier, for communication, collegiality, and productivity in applied data science.

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