Free Download
The DataOps Cookbook
3rd Edition, 2023
The DataOps Cookbook, 3rd Edition: how DataOps applies software and manufacturing practice to turn data chaos into fast, error-free insight. Free download.
Includes actual recipes, too.
- Edition
- 3rd Edition
- Length
- 320 pages
- Price
- Free
About this book
The DataOps Cookbook collects DataKitchen's methods for applying Agile development, DevOps, and lean manufacturing to data analytics. The third edition, subtitled 'Data Journey First DataOps', leads with observing the journey data takes through production — from ingestion through processing to delivered insight — as the fastest route to fewer errors and a working DataOps practice. Chapters are organized by role, covering the chief data officer, data engineer, data scientist, data analyst, and DataOps engineer, and close with case studies and actual food recipes.
Key points
- The DataOps Cookbook applies Agile development, DevOps, and lean manufacturing to data analytics. The third edition runs 320 pages and costs nothing.
- The third edition leads with the Data Journey: watch what happens to data in production, from ingestion to delivered insight, before automating anything.
- Chapters are grouped by role, so a chief data officer, data engineer, data scientist, data analyst, and DataOps engineer each get the part that applies to their job.
- Forty of the book's 62 chapters are published in full on datakitchen.io, linked from the table of contents on this page.
- Nothing in the book requires DataKitchen software: it describes practices, and they work with the tools a team already runs.
- Food recipes from the DataKitchen team are interleaved between the chapters, which is where the company name comes from.
Download Your Free Copy
Complete the form below to get The DataOps Cookbook.
What's inside
62 chapters, most of them published here first: the book's contribution is the selection and the order. Linked titles go straight to the full text, no form required.
Opening
- Preface to the Third Edition
- Introduction
- The DataOps Manifesto
What Is DataOps
- Delivering Analytics at Amazon Speed
- The Seven Steps to Implement DataOps
- DataOps Is NOT Just DevOps for Data
- DataOps Resolves the Struggle Between Centralization and Freedom in Analytics
The Data Journey Manifesto
- The Data Journey Manifesto
- Why the Data Journey Manifesto?
- Five Pillars of Data Journeys
- Data Journey First DataOps
- The Terms and Conditions of a Data Contract Are Data Tests
- “You Complete Me,” Said Data Lineage to Data Journeys
- Two Downs Make Two Ups: The Only Success Metrics That Matter
- DataOps Observability: Taming the Chaos
DataOps for the Chief Data Officer
- Warring Tribes into Winning Teams
- Improving Teamwork in Data Analytics with DataOps
- Eliminate Your Analytics Development Bottlenecks
- Prove Your Awesomeness with Data: The CDO DataOps Dashboard
- Surviving Your Second Year as CDO
- CAOs and CDOs: Earn the Trust of Your CEO
- The Four-Stage Journey to Analytics Excellence
- Pitching a DataOps Project That Matters
DataOps for the Data Engineer
- The “Right to Repair” Data Architecture with DataOps
- Enabling Design Thinking in Data Analytics with DataOps
- DataOps Puts Agility into Agile Data Warehousing
- Speed Up Innovation with DataOps
- How to Inspire Code Reuse in Data Analytics
- Plumbing Wisdom for Data Pipelines
- Data Engineers Are Burned Out and Calling for DataOps
- 10 DataOps Principles for Overcoming Data Engineer Burnout
- The Ten Standard Tools to Develop Data Pipelines in Microsoft Azure
DataOps for the Data Scientist
- A Great Model Is Not Enough: Deploying AI Without Technical Debt
- What Data Scientists Really Need
DataOps for Data Analysts
- DataOps for Business Analytics Teams
- Centralize Your Data Processes with a DataOps Process Hub
- Eight Challenges of Data Analytics
DataOps Engineering
- DataOps Engineer Will Be the Sexiest Job in Analytics
- Building a DataOps Team
- How to Succeed as a DataOps Engineer
- A Day in the Life of a DataOps Engineer
- What Is a DataOps Engineer?
- Improve Business Agility by Hiring a DataOps Engineer
- Why DevOps Tools Fail at DataOps
- What Is a Data Mesh?
- Use DataOps with Your Data Mesh to Prevent Data Mush
- DataOps Is the Factory That Supports Your Data Mesh
- DataOps Enables Your Data Fabric
DataOps for Data Quality
- Disband Your Impact Review Board: Automate Analytics Testing
- Build Trust Through Test Automation and Monitoring
- How Data Analytics Professionals Can Sleep Better
- DataOps TestGen: “Mystery Box Full of Data Errors”
Examples and Case Studies
- Grow Sales Using a DataOps-Powered Customer Data Platform
- Achieving Growth Targets with a DataOps-Powered Customer Data Platform
- How a Mixed Martial Arts Fighter Would Approach Data Analytics
- Reinvent Marketing Automation with DataKitchen DataOps Automation
- Meeting the Product Launch Challenge with DataOps
- Tomorrow’s Forecast: Cloudy with a Chance of Data Errors
Survey and Back Matter
- The Data Engineering Survey, with data.world
- Additional Recipes
- DataOps Resources
- About the Authors
New in the third edition
The third edition is subtitled Data Journey First DataOps. The idea behind it is simple: before you automate anything, watch the journey your data actually takes through production, from ingestion, through processing, to the insight someone acts on. That is where the errors, tool failures, and timing problems surface, and fixing them first buys the credibility to do everything else.
Lower production errors make data more reliable, and a team that is not firefighting has time to automate. The edition adds chapters on the Data Journey Manifesto, the Five Pillars of Data Journeys, treating the terms of a data contract as data tests, how lineage and Data Journeys fit together, and DataOps Observability.
Frequently Asked Questions
Common questions about The DataOps Cookbook
Is The DataOps Cookbook really free?
Yes. The full 320-page PDF costs nothing. Fill in the form on this page and we send you a copy to keep and share. Many of the chapters are also readable on this site for free without any form at all — the table of contents below links to every one that has a web version.
Who is The DataOps Cookbook for?
Data teams and the people who run them. The chapters are grouped by role, so a chief data officer, a data engineer, a data scientist, a data analyst, and a DataOps engineer each get the part of the practice that applies to their own job. It closes with customer case studies and the food recipes.
What is new in the third edition?
The third edition is subtitled Data Journey First DataOps. It leads with observing the journey data takes through production — from ingestion through processing to delivered insight — as the fastest route to fewer errors. New chapters cover the Data Journey Manifesto, the Five Pillars of Data Journeys, data contracts as data tests, the relationship between data lineage and Data Journeys, and DataOps Observability.
Who wrote The DataOps Cookbook?
Christopher Bergh, Gil Benghiat, and Eran Strod. Chris and Gil are two of the three co-founders of DataKitchen, and Eran Strod went on to co-write Recipes for DataOps Success. The first edition of the Cookbook appeared in 2019, the second in 2021, and the third in 2023.
Do I need to buy DataKitchen software to use the book?
No. The Cookbook describes practices, not products — Agile development, DevOps, and lean manufacturing applied to data analytics, and they work with whatever tools you already run. DataKitchen does publish two free open-source tools, DataOps TestGen and DataOps Observability, if you want software to go with the ideas.
Does the book actually contain food recipes?
It does. Recipes contributed by the DataKitchen team are interleaved between the chapters, which is where the company name comes from. They appear in the table of contents above alongside everything else, so you can see exactly what arrives in the PDF.
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