- A combination of technical and domain expertise. Combining the technical expertise of computer scientists and mathematicians, and statisticians, with a critically-important, but often overlooked, element – domain knowledge – can help fuel smarter, data-driven decisions.
- Application of the scientific method to diverse data. Using the model – observe, question, hypothesize, test and analyze – the team can produce an entirely new level of insight and direction from diverse sets of data. For instance, for a financial services firm seeking to deter fraud, this may involve examining connections between payment records and exchange rates.
- A six to nine month rotation of the team’s domain specialists. Armed with institutional knowledge in areas such as financial services, healthcare or defense, these domain specialists can contribute to a stronger understanding of the mission at the data science team level, and importantly, carry back new insights to organization decision makers.
With the explosion of cloud technology and advanced analytics, it’s suddenly possible to pair the diverse, seemingly-unrelated sets of data to attain mission-driving insights. But it’s only with the right data science team – a fusion of technical and domain experts – that organizations can push past the hype of “big data” to “big analytics,” and reach those game-changing insights. Booz Allen Hamilton outlines this approach in an infographic exploring the anatomy of the data science team. Foundational elements of a data science team include: