Log In
Or create an account -> 
Imperial Library
  • Home
  • About
  • News
  • Upload
  • Forum
  • Help
  • Login/SignUp

Index
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
  • ← Prev
  • Back
  • Next →
  • ← Prev
  • Back
  • Next →

Chief Librarian: Las Zenow <zenow@riseup.net>
Fork the source code from gitlab
.

This is a mirror of the Tor onion service:
http://kx5thpx2olielkihfyo4jgjqfb7zx7wxr3sd4xzt26ochei4m6f7tayd.onion