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Big data : understanding how data powers big business / / Bill Schmarzo



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Autore: Schmarzo Bill Visualizza persona
Titolo: Big data : understanding how data powers big business / / Bill Schmarzo Visualizza cluster
Pubblicazione: Indianapolis, IN : , : John Wiley & Sons, , [2013]
©2013
Edizione: 1st edition
Descrizione fisica: 1 online resource (242 p.)
Disciplina: 658.4038
Soggetto topico: Knowledge management
Management information systems
Soggetto genere / forma: Electronic books.
Note generali: Includes index.
Nota di contenuto: 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 Answer Managing 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 Creativity Summary; 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 Drivers Driver #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 Example Summary; 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
Chapter 9 Identifying Big Data Use Cases
Sommario/riassunto: 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
Titolo autorizzato: Big data  Visualizza cluster
ISBN: 1-118-74003-3
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910462982003321
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