Big Data MBA: Driving Business Strategies with Data Science

Author : Bill Schmarzo
Price : Rs 699.00
ISBN 13 : 9788126559657
ISBN 10 : 8126559659
Pages : 312
Type : Paperbound

9788126559657

Details

Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities and create new sources of competitive differentiation.

Introduction

 

Part I Business Potential of Big Data Chapter

Chapter 1 The Big Data Business Mandate

  • Big Data MBA Introduction
  • Focus Big Data on Driving Competitive Differentiation  
  • Leveraging Technology to Power Competitive Differentiation  
  • History Lesson on Economic-Driven Business Transformation
  • Critical Importance of "Thinking Differently"
  • Don't Think Big Data Technology, Think Business Transformation  
  • Don't Think Business Intelligence, Think Data Science
  • Don't Think Data Warehouse, Think Data Lake
  • Don't Think "What Happened," Think "What Will Happen"
  • Don't Think HIPPO, Think Collaboration

 

Chapter 2 Big Data Business Model Maturity Index

  • Introducing the Big Data Business Model Maturity Index
  • Phase 1: Business Monitoring
  • Phase 2: Business Insights
  • Phase 3: Business Optimization
  • Phase 4: Data Monetization
  • Phase 5: Business Metamorphosis
  • Big Data Business Model Maturity Index Lessons Learned
  • Lesson 1: Focus Initial Big Data Efforts Internally
  • Lesson 2: Leverage Insights to Create New Monetization Opportunities
  • Lesson 3: Preparing for Organizational Transformation

 

Chapter 3 The Big Data Strategy Document

  • Establishing Common Business Terminology
  • Introducing the Big Data Strategy Document  
  • Identifying the Organization's Key Business Initiatives
  • What's Important to Chipotle?
  • Identify Key Business Entities and Key Decisions
  • Identify Financial Drivers (Use Cases)
  • Identify and Prioritize Data Sources  
  • Introducing the Prioritization Matrix  
  • Using the Big Data Strategy Document to Win the World Series

 

Chapter 4 The Importance of the User Experience

  • The Unintelligent User Experience
  • Capture the Key Decisions
  • Support the User Decisions
  • Consumer Case Study: Improve Customer Engagement
  • Business Case Study: Enable Frontline Employees
  • Store Manager Dashboard
  • Sample Use Case: Competitive Analysis
  • Additional Use Cases
  • B2B Case Study: Make the Channel More Effective
  • The Advisors Are Your Partners--Make Them Successful
  • Financial Advisor Case Study
  • Informational Sections of Financial Advisor Dashboard
  • Recommendations Section of Financial Advisor Dashboard  

 

Part II Data Science

Chapter 5 Differences Between Business Intelligence and Data Science

  • What Is Data Science?
  • BI Versus Data Science: V The Questions Are Different
  • BI Questions
  • Data Science Questions
  • The Analyst Characteristics Are Different
  • The Analytic Approaches Are Different  
  • Business Intelligence Analyst Engagement Process
  • The Data Scientist Engagement Process
  • The Data Models Are Different
  • Data Modeling for BI
  • Data Modeling for Data Science
  • The View of the Business Is Different

 

Chapter 6 Data Science 101

  • Data Science Case Study Setup
  • Fundamental Exploratory Analytics
  • Trend Analysis
  • Boxplots
  • Geographical (Spatial) Analysis
  • Pairs Plot
  • Time Series Decomposition
  • Analytic Algorithms and Models
  • Cluster Analysis
  • Normal Curve Equivalent (NCE) Analysis
  • Association Analysis
  • Graph Analysis
  • Text Mining  
  • Sentiment Analysis
  • Traverse Pattern Analysis
  • Decision Tree Classifier Analysis
  • Cohorts Analysis

 

Chapter 7 The Data Lake

  • Introduction to the Data Lake
  • Characteristics of a Business-Ready Data Lake
  • Using the Data Lake to Cross the Analytics Chasm
  • Modernize Your Data and Analytics Environment
  • Action #1: Create a Hadoop-Based Data Lake
  • Action #2: Introduce the Analytics Sandbox
  • Action #3: Off-Load ETL Processes from Data Warehouses
  • Analytics Hub and Spoke Analytics Architecture
  • Early Learnings
  • Lesson #1: The Name Is Not Important
  • Lesson #2: It's Data Lake, Not Data Lakes
  • Lesson #3: Data Governance Is a Life Cycle, Not a Project
  • Lesson #4: Data Lake Sits Before Your Data Warehouse, Not After It
  • What Does the Future Hold?

 

Part III Data Science for Business Stakeholders

Chapter 8 Thinking Like a Data Scientist

  • The Process of Thinking Like a Data Scientist
  • Step 1: Identify Key Business Initiative
  • Step 2: Develop Business Stakeholder Personas
  • Step 3: Identify Strategic Nouns
  • Step 4: Capture Business Decisions
  • Step 5: Brainstorm Business Questions
  • Step 8: Putting Analytics into Action

 

Chapter 9 "By" Analysis Technique

  • "By" Analysis Introduction
  • "By" Analysis Exercise
  • Foot Locker Use Case "By" Analysis

 

Chapter 10 Score Development Technique

  • Definition of a Score
  • FICO Score Example
  • Other Industry Score Examples
  • LeBron James Exercise Continued
  • Foot Locker Example Continued

 

Chapter 11 Monetization Exercise

  • Fitness Tracker Monetization Example
  • Step 1: Understand Product Usage
  • Step 2: Develop Stakeholder Personas
  • Step 3: Brainstorm Potential Recommendations
  • Step 4: Identify Supporting Data Sources
  • Step 5: Prioritize Monetization Opportunities
  • Step 6: Develop Monetization Plan

 

Chapter 12 Metamorphosis Exercise

  • Business Metamorphosis Review
  • Business Metamorphosis Exercise
  • Articulate the Business Metamorphosis Vision
  • Understand Your Customers
  • Articulate Value Propositions
  • Define Data and Analytic Requirements
  • Business Metamorphosis in Health Care

 

Part IV Building Cross-Organizational Support

Chapter 13 Power of Envisioning

  • Envisioning: Fueling Creative Thinking
  • Big Data Vision Workshop Process
  • Pre-engagement Research
  • Business Stakeholder Interviews
  • Explore with Data Science
  • Workshop
  • Setting Up the Workshop
  • The Prioritization Matrix

 

Chapter 14 Organizational Ramifications

  • Chief Data Monetization Officer
  • CDMO Responsibilities
  • CDMO Organization
  • Analytics Center of Excellence
  • CDMO Leadership
  • Privacy, Trust and Decision Governance
  • Privacy Issues = Trust Issues
  • Decision Governance
  • Unleashing Organizational Creativity

 

Chapter 15 Stories

  • Customer and Employee Analytics
  • Product and Device Analytics
  • Network and Operational Analytics
  • Characteristics of a Good Business Story

 

Summary

Homework Assignment

Index

Data Scientists, Business Analysts, Data Analysts, Statisticians, Analytics Managers, Business Intelligence Consultants, Data Architects, Web Analysts, Data Miners, Data Engineeers, Data Managers

 

Bill Schmarzo has nearly three decades of experience in data warehousing, Business Intelligence and analytics. Currently, Bill is the CTO of the Enterprise Information Management & Analytics Practice for EMC Global Services. He was the Vice President of Analytics at Yahoo from 2007 to 2008.