The Informed Company: How to Build a Cloud-Based Data Stack to Explore and Understand Data

259 Pages·2021·9.359 MB·English

by  Dave Fowler, Matthew C. David

The Informed Company

The Informed
Company
How to Build Modern Agile Data Stacks
that Drive Winning Insights
Dave Fowler
Matt David
Copyright © 2022 by Dave Fowler and Matt David. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
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Library of Congress Cataloging- in- Publication Data
Names: Fowler, Dave (Computer scientist), author. | Matt David,
author.
Title: The informed company : how to build modern agile data stacks that
drive winning insights / Dave Fowler, Matt David.
Description: Hoboken, New Jersey : Wiley, [2022] | Includes index.
Identifiers: LCCN 2021028324 (print) | LCCN 2021028325 (ebook) | ISBN
9781119748007 (paperback) | ISBN 9781119748021 (adobe pdf) | ISBN
9781119748014 (epub)
Subjects: LCSH: Data structures (Computer science) | Big data. | Cloud
computing.
Classification: LCC QA76.9.D35 F69 2022 (print) | LCC QA76.9.D35 (ebook)
| DDC 005.7/3—dc23
LC record available at https://lccn.loc.gov/2021028324
LC ebook record available at https://lccn.loc.gov/2021028325
Cover image: © Neo Geometric/Shutterstock
Cover design: Wiley
To my mother who continues to be my most supportive and patient
teacher. As a software engineer you taught me to code for my
sixth-grade science project. Today as a Data Analyst you helped a
38-year-old me in discussions and edits of this book. Thank you for
always supporting and encouraging my curiosities and for all your
love.
— Dave Fowler
I dedicate this book to my Mom, an educator who is fueled by help-
ing others learn. Thank you for always believing in me and being an
example of how much you can affect other people’s lives.
— Matt David

Contents
About This Book xiii
Foreword xxi
Introduction xxv
Stage 1 Source (aka Siloed Data) 1
Chapter 1 Starting with Source Data 3
Common Options for Analyzing Source Data 4
Chapter 2 The Need to Replicate Source Data 11
Replicate Sources 12
Create Read-Only Access 14
Chapter 3 Source Data Best Practices 15
Keep a Complexity Wiki Page 15
Snippet Dictionary 16
Use a BI Product 17
Double Check Results 18
Keep Short Dashboards 19
Design Before Building 20
vii
viii Contents
Stage 2 Data Lake (aka Data Combined) 23
Chapter 4 Why Build a Data Lake? 25
What Is a Data Lake? 26
Reasons to Build a Data Lake Summarized 27
Chapter 5 Choosing an Engine for the Data Lake 33
Modern Columnar Warehouse Engines 35
Modern Warehouse Engine Products 38
Database Engines 41
Recommendation 42
Chapter 6 Extract and Load (EL) Data 45
ETL versus ELT 46
EL/ETL Vendors 48
Extract Options 49
Load Options 51
Multiple Schemas 52
Other Extract and Load Routes 53
Chapter 7 Data Lake Security 55
Access in Central Place 56
Permission Tiers 57
Chapter 8 Data Lake Maintenance 59
Why SQL? 60
Data Sources 61
Performance 64
Upgrade Snippets to Views 68