Cover image for Big Data : Understanding How Data Powers Big Business.
Big Data : Understanding How Data Powers Big Business.
Title:
Big Data : Understanding How Data Powers Big Business.
Author:
Schmarzo, William D.
ISBN:
9781118740033
Personal Author:
Edition:
1st ed.
Physical Description:
1 online resource (242 pages)
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 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 -- The Big Data Envisioning Process -- Step 1: Research Business Initiatives -- Step 2: Acquire and Analyze Your Data -- Step 3: Ideation Workshop: Brainstorm New Ideas -- Step 4: Ideation Workshop: Prioritize Big Data Use Cases -- Step 5: Document Next Steps -- The Prioritization Process -- The Prioritization Matrix Process -- Prioritization Matrix Traps -- Using User Experience Mockups to Fuel the Envisioning Process -- Summary -- Chapter 10 Solution Engineering -- The Solution Engineering Process.

Step 1: Understand How the Organization Makes Money -- Step 2: Identify Your Organization's Key Business Initiatives -- Step 3: Brainstorm Big Data Business Impact -- Step 4: Break Down the Business Initiative Into Use Cases -- Step 5: Prove Out the Use Case -- Step 6: Design and Implement the Big Data Solution -- Solution Engineering Tomorrow's Business Solutions -- Customer Behavioral Analytics Example -- Predictive Maintenance Example -- Marketing Effectiveness Example -- Fraud Reduction Example -- Network Optimization Example -- Reading an Annual Report -- Financial Services Firm Example -- Retail Example -- Brokerage Firm Example -- Summary -- Chapter 11 Big Data Architectural Ramifications -- Big Data: Time for a New Data Architecture -- Introducing Big Data Technologies -- Apache Hadoop -- Hadoop MapReduce -- Apache Hive -- Apache HBase -- Pig -- New Analytic Tools -- New Analytic Algorithms -- Bringing Big Data into the Traditional Data Warehouse World -- Data Enrichment: Think ELT, Not ETL -- Data Federation: Query is the New ETL -- Data Modeling: Schema on Read -- Hadoop: Next Gen Data Staging and Prep Area -- MPP Architectures: Accelerate Your Data Warehouse -- In-database Analytics: Bring the Analytics to the Data -- Cloud Computing: Providing Big Data Computational Power -- Summary -- Chapter 12 Launching Your Big Data Journey -- Explosive Data Growth Drives Business Opportunities -- Traditional Technologies and Approaches Are Insufficient -- The Big Data Business Model Maturity Index -- Driving Business and IT Stakeholder Collaboration -- Operationalizing Big Data Insights -- Big Data Powers the Value Creation Process -- Summary -- Chapter 13 Call to Action -- Identify Your Organization's Key Business Initiatives -- Start with Business and IT Stakeholder Collaboration.

Formalize Your Envisioning Process -- Leverage Mockups to Fuel the Creative Process -- Understand Your Technology and Architectural Options -- Build off Your Existing Internal Business Processes -- Uncover New Monetization Opportunities -- Understand the Organizational Ramifications -- Index.
Abstract:
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 how-to guide to leveraging big data to drive business value. Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data. Shows how to decompose current business strategies in order to link big data initiatives to the organization's value creation processes Explores different value creation processes and models Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles Provides methodology worksheets and exercises so readers can apply techniques Includes real-world examples from a variety of organizations leveraging big data Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Electronic Access:
Click to View
Holds: Copies: