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Data Lakes For Dummies Alan R. Simon (Arizona State University)

Data Lakes For Dummies By Alan R. Simon (Arizona State University)

Data Lakes For Dummies by Alan R. Simon (Arizona State University)


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Data Lakes For Dummies Summary

Data Lakes For Dummies by Alan R. Simon (Arizona State University)

Take a dive into data lakes

Data lakes is the latest buzz word in the world of data storage, management, and analysis.Data LakesForDummiesdecodesand demystifies the conceptand helps youget a straightforwardanswer the question:Whatexactlyis a datalakeand do I need one for my business? Written for an audience oftechnology decision makers tasked with keeping up with the latest and greatest data options,this bookprovides the perfectintroductory surveyofthese noveland growingfeatures of the information landscape.Itexplainshow they can helpyourbusiness, what they can (and cant) achieve, andwhat you need to do tocreatethelakethat best suitsyourparticular needs.

With a minimum of jargon,prolific tech author andbusiness intelligenceconsultant Alan Simonexplainshowdata lakes differ fromotherdatastorageparadigms. Once youve got the background picture, he maps out ways you can add a data lake to yourbusiness systems;migrate existing informationand switchon the fresh data supply;clean up the product;and open channels to thebestintelligence software forto interpretingwhat youvestored.

  • Understand and build data lake architecture
  • Store,clean, and synchronizenew and existing data
  • Comparethe bestdata lake vendors
  • Structure raw data and produce usable analytics

Whatever your business,data lakes are going to form evermore prominentparts of theinformationuniverseevery business should have access to.Diveintothis booktostartexploring thedeepcompetitive advantagethey make possibleandmakesure your businessisntleft standing on the shore.

About Alan R. Simon (Arizona State University)

Alan Simon is the managing principal of Thinking Helmet, Inc., the author of 32 books on business technology, and a consultant whos worked with enterprise and government organizations. His professional focus is business intelligence, analytics, and data warehousing. He also teaches university courses in his specialty areas.

Table of Contents

Introduction 1

Part 1: Getting Started with Data Lakes 5

Chapter 1: Jumping into the Data Lake 7

Chapter 2: Planning Your Day (and the Next Decade) at the Data Lake 25

Chapter 3: Break Out the Life Vests: Tackling Data Lake Challenges 49

Part 2: Building the Docks, Avoiding the Rocks 65

Chapter 4: Imprinting Your Data Lake on a Reference Architecture 67

Chapter 5: Anybody Hungry? Ingesting and Storing Raw Data in Your Bronze Zone 97

Chapter 6: Your Data Lakes Water Treatment Plant: The Silver Zone 121

Chapter 7: Bottling Your Data Lake Water in the Gold Zone 139

Chapter 8: Playing in the Sandbox 151

Chapter 9: Fishing in the Data Lake 159

Chapter 10: Rowing End-to-End across the Data Lake 169

Part 3: Evaporating the Data Lake into the Cloud 187

Chapter 11: A Cloudy Day at the Data Lake 189

Chapter 12: Building Data Lakes in Amazon Web Services 199

Chapter 13: Building Data Lakes in Microsoft Azure 217

Part 4: Cleaning Up the Polluted Data Lake 243

Chapter 14: Figuring Out If You Have a Data Swamp Instead of a Data Lake 245

Chapter 15: Defining Your Data Lake Remediation Strategy 259

Chapter 16: Refilling Your Data Lake 283

Part 5: Making Trips to the Data Lake a Tradition 297

Chapter 17: Checking Your GPS: The Data Lake Road Map 299

Chapter 18: Booking Future Trips to the Data Lake 325

Part 6: The Part of Tens 333

Chapter 19: Top Ten Reasons to Invest in Building a Data Lake 335

Chapter 20: Ten Places to Get Help for Your Data Lake 341

Chapter 21: Ten Differences between a Data Warehouse and a Data Lake 345

Index 351

Additional information

NGR9781119786160
9781119786160
1119786169
Data Lakes For Dummies by Alan R. Simon (Arizona State University)
New
Paperback
John Wiley & Sons Inc
2021-08-23
384
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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