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Disruptive Analytics

Charting Your Strategy for Next-Generation Business Analytics

  • Thomas W. Dinsmore

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Thomas W. Dinsmore
    Pages 1-21
  3. Thomas W. Dinsmore
    Pages 23-46
  4. Thomas W. Dinsmore
    Pages 47-71
  5. Thomas W. Dinsmore
    Pages 73-96
  6. Thomas W. Dinsmore
    Pages 97-116
  7. Thomas W. Dinsmore
    Pages 117-144
  8. Thomas W. Dinsmore
    Pages 145-167
  9. Thomas W. Dinsmore
    Pages 169-198
  10. Thomas W. Dinsmore
    Pages 199-230
  11. Thomas W. Dinsmore
    Pages 231-251
  12. Back Matter
    Pages 253-262

About this book

Introduction

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 Learn

  • Discover how the open source business model works and how to make it work for you
  • See how cloud computing completely changes the economics of analytics
  • Harness the power of Hadoop and its ecosystem
  • Find out why Apache Spark is everywhere
  • Discover the potential of streaming and real-time analytics
  • Learn what Deep Learning can do and why it matters
  • See how self-service analytics can change the way organizations do business
Who This Book Is For

Corporate 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.

Keywords

predictive analytics business intelligence Hadoop deep learning geospatial analytics columnar databases data warehouse appliances sentiment analysis credit risk analysis ensemble models Lambda arcitecture Kaizen

Authors and affiliations

  • Thomas W. Dinsmore
    • 1
  1. 1.NewtonUSA

Bibliographic information