Data Engineering Teams by Anderson, Jesse -- Read -- Imperial Library of Trantor

Index

Data Engineering Teams Introduction

About This Book Warnings and Success Stories Who Should Read This Navigating the Book Chapters Conventions Used in This Book Big Data Why Is Big Data So Much More Complicated? Distributed Systems Are Hard What Does It All Mean, Basil? What Does It Mean for Software Engineering Teams? What Does It Mean for Data Warehousing Teams? What Is a Data Engineering Team? Skills Needed in a Team Skills Gap Analysis Skill Gap Analysis Results What I Look for in Data Engineering Teams Operations Quality Assurance What Is a Data Engineer? What I Look for in Data Engineers Qualified Data Engineers Not Just Data Warehousing and DBAs Ability Gap Themes and Thoughts of a Data Engineering Team Hub of the Wheel How to Work with a Data Science Team How to Work with a Data Warehousing Team How to Work with an Analytics and/or Business Intelligence Team How I Evaluate Teams Equipment and Resources Thought Frameworks Building Data Pipelines Knowledge of Use Case Right Tool for the Job Crawl, Walk, Run Technologies Why Do Teams Fail? Why Do Teams Succeed? Paying the Piper Some Technologies Are Just Dead Ends What if You Have Gaps and Still Have to Do It? Pre-project Steps Use Case Evaluate the Team Choose the Technologies Write the Code Evaluate Repeat Probability of Success

Conclusion

Best Efforts About the Author

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