Data Lakes For Dummies
- Length: 384 pages
- Edition: 1
- Language: English
- Publisher: For Dummies
- Publication Date: 2021-07-14
- ISBN-10: 1119786169
- ISBN-13: 9781119786160
- Sales Rank: #158291 (See Top 100 Books)
Take a dive into data lakes
“Data lakes” is the latest buzz word in the world of data storage, management, and analysis. Data Lakes For Dummies decodes and demystifies the concept and helps you get a straightforward answer the question: “What exactly is a data lake and do I need one for my business?” Written for an audience of technology decision makers tasked with keeping up with the latest and greatest data options, this book provides the perfect introductory survey of these novel and growing features of the information landscape. It explains how they can help your business, what they can (and can’t) achieve, and what you need to do to create the lake that best suits your particular needs.
With a minimum of jargon, prolific tech author and business intelligence consultant Alan Simon explains how data lakes differ from other data storage paradigms. Once you’ve got the background picture, he maps out ways you can add a data lake to your business systems; migrate existing information and switch on the fresh data supply; clean up the product; and open channels to the best intelligence software for to interpreting what you’ve stored.
- Understand and build data lake architecture
- Store, clean, and synchronize new and existing data
- Compare the best data lake vendors
- Structure raw data and produce usable analytics
Whatever your business, data lakes are going to form ever more prominent parts of the information universe every business should have access to. Dive into this book to start exploring the deep competitive advantage they make possible―and make sure your business isn’t left standing on the shore.
Cover Title Page Copyright Table of Contents Introduction About This Book Foolish Assumptions Icons Used in This Book Beyond the Book Where to Go from Here Part 1: Getting Started with Data Lakes Chapter 1: Jumping into the Data Lake What Is a Data Lake? The Data Lake Olympics Data Lakes and Big Data The Data Lake Water Gets Murky Chapter 2: Planning Your Day (and the Next Decade) at the Data Lake Carpe Diem: Seizing the Day with Big Data Managing Equal Opportunity Data Building Today’s — and Tomorrow’s — Enterprise Analytical Data Environment Reducing Existing Stand-Alone Data Marts Eliminating Future Stand-Alone Data Marts Establishing a Migration Path for Your Data Warehouses Aligning Data with Decision Making Speedboats, Canoes, and Lake Cruises: Traversing the Variable-Speed Data Lake Managing Overall Analytical Costs Chapter 3: Break Out the Life Vests: Tackling Data Lake Challenges That’s Not a Data Lake, This Is a Data Lake! Exposing Data Lake Myths and Misconceptions Navigating Your Way through the Storm on the Data Lake Building the Data Lake of Dreams Performing Regular Data Lake Tune-ups — Or Else! Technology Marches Forward Part 2: Building the Docks, Avoiding the Rocks Chapter 4: Imprinting Your Data Lake on a Reference Architecture Playing Follow the Leader Guiding Principles of a Data Lake Reference Architecture A Reference Architecture for Your Data Lake Reference Architecture Incoming! Filling Your Data Lake Supporting the Fleet Sailing on Your Data Lake The Old Meets the New at the Data Lake Bringing Outside Water into Your Data Lake Playing at the Edge of the Lake Chapter 5: Anybody Hungry? Ingesting and Storing Raw Data in Your Bronze Zone Ingesting Data with the Best of Both Worlds Joining the Data Ingestion Fraternity Storing Data in Your Bronze Zone Just Passing Through: The Cross-Zone Express Lane Taking Inventory at the Data Lake Bringing Analytics to Your Bronze Zone Chapter 6: Your Data Lake’s Water Treatment Plant: The Silver Zone Funneling Data further into the Data Lake Bringing Master Data into Your Data Lake Impacting the Bronze Zone Getting Clever with Your Storage Options Working Hand-in-Hand with Your Gold Zone Chapter 7: Bottling Your Data Lake Water in the Gold Zone Laser-Focusing on the Purpose of the Gold Zone Looking Inside the Gold Zone Deciding What Data to Curate in Your Gold Zone Seeing What Happens When Your Curated Data Becomes Less Useful Chapter 8: Playing in the Sandbox Developing New Analytical Models in Your Sandbox Comparing Different Data Lake Architectural Options Experimenting and Playing Around with Data Chapter 9: Fishing in the Data Lake Starting with the Latest Guidebook Taking It Easy at the Data Lake Staying in Your Lane Doing a Little Bit of Exploring Putting on Your Gear and Diving Underwater Chapter 10: Rowing End-to-End across the Data Lake Keeping versus Discarding Data Components Getting Started with Your Data Lake Shifting Your Focus to Data Ingestion Finishing Up with the Sandbox Part 3: Evaporating the Data Lake into the Cloud Chapter 11: A Cloudy Day at the Data Lake Rushing to the Cloud Running through Some Cloud Computing Basics The Big Guys in the Cloud Computing Game Chapter 12: Building Data Lakes in Amazon Web Services The Elite Eight: Identifying the Essential Amazon Services Looking at the Rest of the Amazon Data Lake Lineup Building Data Pipelines in AWS Chapter 13: Building Data Lakes in Microsoft Azure Setting Up the Big Picture in Azure The Magnificent Seven, Azure Style Filling Out the Azure Data Lake Lineup Assembling the Building Blocks Part 4: Cleaning Up the Polluted Data Lake Chapter 14: Figuring Out If You Have a Data Swamp Instead of a Data Lake Designing Your Report Card and Grading System Looking at the Raw Data Lockbox Knowing What to Do When Your Data Lake Is Out of Order Too Fast, Too Slow, Just Right: Dealing with Data Lake Velocity and Latency Dividing the Work in Your Component Architecture Tallying Your Scores and Analyzing the Results Chapter 15: Defining Your Data Lake Remediation Strategy Setting Your Key Objectives Doing Your Gap Analysis Identifying Resolutions Establishing Timelines Defining Your Critical Success Factors Chapter 16: Refilling Your Data Lake The Three S’s: Setting the Stage for Success Refining and Enriching Existing Raw Data Making Better Use of Existing Refined Data Building New Pipelines with Newly Ingested Raw Data Part 5: Making Trips to the Data Lake a Tradition Chapter 17: Checking Your GPS: The Data Lake Road Map Getting an Overhead View of the Road to the Data Lake Assessing Your Current State of Data and Analytics Putting Together a Lofty Vision Building Your Data Lake Architecture Deciding on Your Kickoff Activities Expanding Your Data Lake Chapter 18: Booking Future Trips to the Data Lake Searching for the All-in-One Data Lake Spreading Artificial Intelligence Smarts throughout Your Data Lake Part 6: The Part of Tens Chapter 19: Top Ten Reasons to Invest in Building a Data Lake Supporting the Entire Analytics Continuum Bringing Order to Your Analytical Data throughout Your Enterprise Retiring Aging Data Marts Bringing Unfulfilled Analytics Ideas out of Dry Dock Laying a Foundation for Future Analytics Providing a Region for Experimentation Improving Your Master Data Efforts Opening Up New Business Possibilities Keeping Up with the Competition Getting Your Organization Ready for the Next Big Thing Chapter 20: Ten Places to Get Help for Your Data Lake Cloud Provider Professional Services Major Systems Integrators Smaller Systems Integrators Individual Consultants Training Your Internal Staff Industry Analysts Data Lake Bloggers Data Lake Groups and Forums Data-Oriented Associations Academic Resources Chapter 21: Ten Differences between a Data Warehouse and a Data Lake Types of Data Supported Data Volumes Different Internal Data Models Architecture and Topology ETL versus ELT Data Latency Analytical Uses Incorporating New Data Sources User Communities Hosting Index About the Author Connect with Dummies End User License Agreement
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