Big Data : Understanding How Data Powers Big Business.

Big Data : Understanding How Data Powers Big Business.

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Bibliographic Details
Author / Creator:Schmarzo, Bill.
Imprint:Hoboken : Wiley, 2013.
©2013
Description:1 online resource (242 pages)
Language:English
Subject:
Big data -- Social aspects.
Data mining -- Social aspects.
Electronic information resources -- Social aspects.
Big data -- Social aspects
Data mining -- Social aspects
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/13616465
Hidden Bibliographic Details
ISBN:9781118740033
1118740033
9781118740002
1118740009
9781119701859
1119701856
9781118739570
1118739574
Notes:English.
Print version record.
Summary:Leverage big data to add value to your business Social media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. Big Data: Understanding How Data Powers Big Business is a complete.
Other form:Print version: Schmarzo, Bill. Big Data : Understanding How Data Powers Big Business. Hoboken : Wiley, ©2013 9781118739570
Table of Contents:
  • Cover; Title Page; Copyright; Contents; Chapter 1 The Big Data Business Opportunity; The Business Transformation Imperative; Walmart Case Study; The Big Data Business Model Maturity Index; Business Monitoring; Business Insights; Business Optimization; Data Monetization; Business Metamorphosis; Big Data Business Model Maturity Observations; Summary; Chapter 2 Big Data History Lesson; Consumer Package Goods and Retail Industry Pre-1988; Lessons Learned and Applicability to Today's Big Data Movement; Summary; Chapter 3 Business Impact of Big Data.
  • Big Data Impacts: The Questions Business Users Can AnswerManaging Using the Right Metrics; Data Monetization Opportunities; Digital Media Data Monetization Example; Digital Media Data Assets and Understanding Target Users; Data Monetization Transformations and Enrichments; Summary; Chapter 4 Organizational Impact of Big Data; Data Analytics Lifecycle; Data Scientist Roles and Responsibilities; Discovery; Data Preparation; Model Planning; Model Building; Communicate Results; Operationalize; New Organizational Roles; User Experience Team; New Senior Management Roles.
  • Liberating Organizational CreativitySummary; Chapter 5 Understanding Decision Theory; Business Intelligence Challenge; The Death of Why; Big Data User Interface Ramifications; The Human Challenge of Decision Making; Traps in Decision Making; What Can One Do?; Summary; Chapter 6 Creating the Big Data Strategy; The Big Data Strategy Document; Customer Intimacy Example; Turning the Strategy Document into Action; Starbucks Big Data Strategy Document Example; San Francisco Giants Big Data Strategy Document Example; Summary; Chapter 7 Understanding Your Value Creation Process.
  • Understanding the Big Data Value Creation DriversDriver #1: Access to More Detailed Transactional Data; Driver #2: Access to Unstructured Data; Driver #3: Access to Low-latency (Real-Time) Data; Driver #4: Integration of Predictive Analytics; Big Data Envisioning Worksheet; Big Data Business Drivers: Predictive Maintenance Example; Big Data Business Drivers: Customer Satisfaction Example; Big Data Business Drivers: Customer Micro-segmentation Example; Michael Porter's Valuation Creation Models; Michael Porter's Five Forces Analysis; Michael Porter's Value Chain Analysis.
  • Value Creation Process: Merchandising ExampleSummary; Chapter 8 Big Data User Experience Ramifications; The Unintelligent User Experience; Understanding the Key Decisions to Build a Relevant User Experience; Using Big Data Analytics to Improve Customer Engagement; Uncovering and Leveraging Customer Insights; Rewiring Your Customer Lifecycle Management Processes; Using Customer Insights to Drive Business Profitability; Big Data Can Power a New Customer Experience; B2C Example: Powering the Retail Customer Experience; B2B Example: Powering Small- and Medium-Sized Merchant Effectiveness; Summary.

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