Big Data: Understanding How Data Powers Big Business (MISL-WILEY)
|Book Title:||Big Data: Understanding How Data Powers Big Business (MISL-WILEY)|
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Overview of Big Data: Understanding How Data Powers Big Business (MISL-WILEY) Book
This book provides "how to" advice and a series of pragmatic methodologies (with accompanying hands-on exercises) for helping organizations leverage big data analytics to power, or re-wire, their value chains. Organizations struggle identifying where and how to leverage these new structured and unstructured data sources and new big data technology innovations to delivery business value. Consequently, many organizations default to taking a technology-led approach to their big data strategies. Leading companies find ways to leverage data -- especially new sources of data -- to tease out new insights about their customers, products, operations, competitors and markets. And these organizations leverage these insights to improve their customer experiences, create new, more compelling products and create new sources of competitive differentiation. Special Features Big data and data science are at the forefront of technology and business initiativesHands-on guide full of real-world techniques, examples of different organizations and what they are doing in the big data space, and methodology worksheets and exercises so that readers can understand and apply the tenants immediately within their organizationsTable of Content Preface Introduction 1 The Big Data Business Opportunity Walmart Case Study Business Monitoring Business Insights Data Monetization Business Metamorphosis Big Data Business Model Maturity Observations Summary 2 Big Data History Lesson Consumer Package Goods and Retail Industry Pre-1988 Lessons Learned and Applicability to Today's Big Data Movement Summary 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 4 Organizational Impact of Big Data Data Analytics Lifecycle Data Scientist Roles and Responsibilities Discovery Data Preparation Model Planning Model Building Communicate Results and more...
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