Data teams : a unified management model for successful data-focused teams / Jesse Anderson.

Format:

Book

Author/Creator:

Anderson, Jesse, author.

Language:

English

Subjects (All):

Big data.

Database management.

Electronic data processing departments--Management.

Electronic data processing departments.

Physical Description:

1 online resource (300 pages)

Edition:

1st ed. 2020.

Place of Publication:

[Place of publication not identified] : Apress, [2020]

System Details:

text file

Summary:

Learn how to run successful big data projects, how to resource your teams, and how the teams should work with each other to be cost effective. This book introduces the three teams necessary for successful projects, and what each team does. Most organizations fail with big data projects and the failure is almost always blamed on the technologies used. To be successful, organizations need to focus on both technology and management. Making use of data is a team sport. It takes different kinds of people with different skill sets all working together to get things done. In all but the smallest projects, people should be organized into multiple teams to reduce project failure and underperformance. This book focuses on management. A few years ago, there was little to nothing written or talked about on the management of big data projects or teams. Data Teams shows why management failures are at the root of so many project failures and how to proactively prevent such failures with your project. You will: Discover the three teams that you will need to be successful with big data Understand what a data scientist is and what a data science team does Understand what a data engineer is and what a data engineering team does Understand what an operations engineer is and what an operations team does Know how the teams and titles differ and why you need all three teams Recognize the role that the business plays in working with data teams and how the rest of the organization contributes to successful data projects.

Contents:

Part 1: Introducing Data Teams

Chapter 1: Data Teams

Chapter 2: The Good, the Bad, and the Ugly Data Teams

Part 2: Building Your Data Team

Chapter 3: The Data Science Team

Chapter 4: The Data Engineering Team

Chapter 5: The Operations Team

Chapter 6: Specialized Staff

Part 3: Working Together and Managing the Data Teams

Chapter 7: Working as a Data Team

Chapter 8: How the Business Interacts with Data Teams

Chapter 9: Managing Big Data Projects

Chapter 10: Starting a Team

Chapter 11: The Steps for Successful Big Data Projects

Chapter 12: Organizational Changes

Chapter 13: Diagnosing and Fixing Problems

Part 4: Case Studies and Interviews

Chapter 14: Interview with Eric Colson and Brad Klingenberg, Stitch Fix

Chapter 15: Interview with Dmitriy Ryaboy, Twitter, Cloudera, Zymergen

Chapter 16: Interview with Bas Geerdink, ING, Rabobank

Chapter 17: Interview with Harvinder Atwal, Moneysupermarket

Chapter 18: Interview with a Large British Telecommunications Company

Chapter 19: Interview with Mikio Braun, Zalando.-.

Notes:

Description based on print version record.

Includes index.

ISBN:

9781484262283

148426228X

OCLC:

1220951795