Book Image

Building Analytics Teams

By : John K. Thompson
5 (1)
Book Image

Building Analytics Teams

5 (1)
By: John K. Thompson

Overview of this book

In Building Analytics Teams, John K. Thompson, with his 30+ years of experience and expertise, illustrates the fundamental concepts of building and managing a high-performance analytics team, including what to do, who to hire, projects to undertake, and what to avoid in the journey of building an analytically sound team. The core processes in creating an effective analytics team and the importance of the business decision-making life cycle are explored to help achieve initial and sustainable success. The book demonstrates the various traits of a successful and high-performing analytics team and then delineates the path to achieve this with insights on the mindset, advanced analytics models, and predictions based on data analytics. It also emphasizes the significance of the macro and micro processes required to evolve in response to rapidly changing business needs. The book dives into the methods and practices of managing, developing, and leading an analytics team. Once you've brought the team up to speed, the book explains how to govern executive expectations and select winning projects. By the end of this book, you will have acquired the knowledge to create an effective business analytics team and develop a production environment that delivers ongoing operational improvements for your organization.
Table of Contents (14 chapters)
12
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13
Index

The general data science process

Data science projects have a general process that the majority of well-run projects follow. Let's outline the overall data science approach to a project to ensure that we have a shared understanding of the approach. The structure of the team is irrelevant to this process. Any data science team will execute a project process for most data science-related projects that are similar to the following list of steps:

  1. Project ideation
  2. Engagement with project sponsors and subject matter experts
  3. Project charter initiation
  4. Project charter refinement
  5. Project management
  6. Convening team meetings
  7. Obtaining internal and external data
  8. Testing various analytical techniques
  9. Building analytical models
  10. Designing the user interface (UI) and user experience (UX)
  11. Presenting interim results
  12. Discussing the level of success or failure in the modeling process
  13. Planning for the testing of models...