LEADER 04547nam 2200685 a 450 001 9910141363103321 005 20211202165114.0 010 $a1-119-20500-X 010 $a1-283-85145-8 010 $a1-118-22582-1 035 $a(CKB)2670000000281695 035 $a(EBL)821833 035 $a(OCoLC)819601893 035 $a(SSID)ssj0000827607 035 $a(PQKBManifestationID)12323482 035 $a(PQKBTitleCode)TC0000827607 035 $a(PQKBWorkID)10830058 035 $a(PQKB)11691631 035 $a(DLC) 2012033118 035 $a(Au-PeEL)EBL821833 035 $a(CaPaEBR)ebr10630556 035 $a(CaONFJC)MIL416395 035 $a(OCoLC)806291900 035 $a(PPN)262293196 035 $a(CaSebORM)9781118239049 035 $a(MiAaPQ)EBC821833 035 $a(EXLCZ)992670000000281695 100 $a20120814d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBig data analytics$b[electronic resource] $eturning big data into big money /$fFrank Ohlhorst 205 $a1st edition 210 $aHoboken, N.J. $cWiley$dc2013 215 $a1 online resource (176 p.) 225 1 $aWiley & SAS business series 300 $aIncludes index. 311 $a1-118-23904-0 311 $a1-118-14759-6 327 $aBig Data Analytics: Turning Big Data into Big Money; Copyright; Contents; Preface; Acknowledgments; Chapter 1: What Is Big Data?; The Arrival of Analytics; Where Is the Value?; More to Big Data Than Meets the Eye; Dealing with the Nuances of Big Data; An Open Source Brings Forth Tools; Caution: Obstacles Ahead; Chapter 2: Why Big Data Matters; Big Data Reaches Deep; Obstacles Remain; Data Continue to Evolve; Data and Data Analysis Are Getting More Complex; The Future Is Now; Chapter 3: Big Data and the Business Case; Realizing Value; The Case for Big Data; The Rise of Big Data Options 327 $aBeyond HadoopWith Choice Come Decisions; Chapter 4: Building the Big Data Team; The Data Scientist; The Team Challenge; Different Teams, Different Goals; Don't Forget the Data; Challenges Remain; Teams versus Culture; Gauging Success; Chapter 5: Big Data Sources; Hunting for Data; Setting the Goal; Big Data Sources Growing; Diving Deeper into Big Data Sources; A Wealth of Public Information; Getting Started with Big Data Acquisition; Ongoing Growth, No End in Sight; Chapter 6: The Nuts and Bolts of Big Data; The Storage Dilemma; Building a Platform; Bringing Structure to Unstructured Data 327 $aProcessing PowerChoosing among In-house, Outsourced, or Hybrid Approaches; Chapter 7: Security, Compliance, Auditing, and Protection; Pragmatic Steps to Securing Big Data; Classifying Data; Protecting Big Data Analytics; Big Data and Compliance; The Intellectual Property Challenge; Chapter 8: The Evolution of Big Data; Big Data: The Modern Era; Today, Tomorrow, and the Next Day; Changing Algorithms; Chapter 9: Best Practices for Big Data Analytics; Start Small with Big Data; Thinking Big; Avoiding Worst Practices; Baby Steps; The Value of Anomalies; Expediency versus Accuracy 327 $aIn-Memory ProcessingChapter 10: Bringing It All Together; The Path to Big Data; The Realities of Thinking Big Data; Hands-on Big Data; The Big Data Pipeline in Depth; Big Data Visualization; Big Data Privacy; Appendix: Supporting Data; ""The MapR Distribution for Apache Hadoop""; ""High Availability: No Single Points of Failure""; About the Author; Index 330 $aUnique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new bu 410 0$aWiley and SAS business series. 606 $aBusiness intelligence 606 $aData mining 615 0$aBusiness intelligence. 615 0$aData mining. 676 $a658.4/72 700 $aOhlhorst$b Frank$f1964-$0851494 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910141363103321 996 $aBig data analytics$91901095 997 $aUNINA