Disruptive Analytics

Charting Your Strategy for Next-Generation Business Analytics

AvThomas W. Dinsmore

Häftad, Engelska, 2016

355 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Fler format och utgåvor

E-bok

472 kr

Beskrivning

Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities.Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization.Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today.What You'll LearnDiscover how the open source business model works and how to make it work for youSee how cloud computing completely changes the economics of analyticsHarness the power of Hadoop and its ecosystemFind out why Apache Spark is everywhereDiscover the potential of streaming and real-time analyticsLearn what Deep Learning can do and why it mattersSee how self-service analytics can change the way organizations do businessWho This Book Is ForCorporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.

Produktinformation

Utgivningsdatum:2016-08-28
Mått:155 x 235 x 21 mm
Vikt:434 g
Format:Häftad
Språk:Engelska
Antal sidor:262
Förlag:APress
ISBN:9781484213124

Utforska kategorier

Ledarskapsböcker inom Ekonomi och Ledarskap
Matematisk statistik inom Naturvetenskap och teknik
Databaser inom Data och IT

Mer om författaren

Thomas W. Dinsmore is Knowledge Expert in Customer Analytics at The Boston Consulting Group. He previously served as Director of Product Management for Revolution Analytics; Analytics Solution Architect for IBM Big Data Solutions; and Principal Consultant for SAS Professional Services. Dinsmore has more than twenty-five years of experience in predictive analytics. He led or contributed to analytic solutions for more than five hundred clients across vertical markets—including AT&T, Banco Santander, Citibank, Dell, J. C. Penney, Monsanto, Morgan Stanley, Office Depot, Sony, Staples, United Health Group, UBS, and Vodafone—and around the world—including the United States, Puerto Rico, Canada, Mexico, Venezuela, Brazil, Chile, the United Kingdom, Belgium, Spain, Italy, Turkey, Israel, Malaysia, and Singapore. Although his roots are in hands-on customer analytics, in the past fifteen years Dinsmore has expanded the scope of his experience to include analytic software applications and broader solutions including database integration and web applications. As a project lead, he has worked with DB2, Oracle, Netezza, SQL Server, and Teradata. Dinsmore is certified in SAS 9 and has working experience with the Hadoop ecosystem and the leading analytic tools in the market today, including SAS, R, SPSS, and Oracle Data Mining. Dinsmore is the author of Modern Analytics Methodologies (FT Press, 2014) and Advanced Analytics Methodologies (FT Press, 2014) and runs The Big Analytics Blog. He holds his MBA from the Wharton School, The University of Pennsylvania, and his bachelor’s from Boston University.

Innehållsförteckning

Chapter 1: Disruption.- Chapter 2: A Short History of Business Analytics.- Chapter 3: Open Source Analytics.- Chapter 4: The Hadoop Ecosystem.- Chapter 5: In-Memory Analytics.- Chapter 6: Streaming and Real Time.- Chapter 7: Analytics in the Cloud.- Chapter 8: Machine Learning.- Chapter 9: Self-Service Analytics.- Chapter 10: Handbook for Managers.