How well prepared is your organization to innovate, using data science? In this report, two leading data scientists at the consulting firm Booz Allen Hamilton describe ten characteristics of a mature data science capability. After spending years helping clients such as the US government and commercial organizations worldwide build innovative data science capabilities, Peter Guerra and Dr. Kirk Borne identified these characteristics to help you measure your company’s competence in this area.
This report provides a detailed discussion of each of the 10 signs of data science maturity, which—among many other things—encourage you to:
- Give members of your organization access to all your available data
- Use Agile and leverage "DataOps"—DevOps for data product development
- Help your data science team sharpen its skills through open or internal competitions
- Personify data science as a way of doing things, and not a thing to do
Table of contents
1. Ten Signs of a Mature Data Science Capability
A mature data science organization…
- …democratizes all data and data access.
- …uses Agile for everything and leverages DataOps (i.e., DevOps for Data Product Development).
- …leverages the crowd and works collaboratively with businesses (i.e., data champions, hackathons, etc.).
- …follows rigorous scientific methodology (i.e., measured, experimental, disciplined, iterative, refining hypotheses as needed).
- …attracts and retains diverse participants, and grants them freedom to explore.
- …relentlessly asks the right questions, and constantly searches for the next one.
- …celebrates a fast-fail collaborative culture.
- …shows insights through illustrations and tells stories.
- …builds proof of value, not proof of concepts.
- …personifies data science as a way of doing things, not a thing to do.
- A mature data science organization…
- Title: Ten Signs of Data Science Maturity
- Release date: March 2016
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491952511
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