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The Data to DollarsT Value Chain: A Practical Guide to Business Analytics provides guidance on how to create successful analytics projects, assemble teams, and plan for ongoing initiatives. The book is a thoughtful, skilled, technical and analytical guide on the methods used to truly understand customers, consumer behavior, and market opportunities. This practical guide contains all components of the process, along with the methods and templates needed to unlock the potential of data. Readers will learn how to "reduce the barrier to benefit" from analytics by enabling their team to get more from their analytics efforts despite budget constraints, how to staff talent and experience, how to use knowledge, and how to recognize data quality, availability, and potential political barriers within an organization. Includes the methodology to reduce risk, avoid failure, and enhance the results of analytics projects Unlocks the full potential of data with best practices, practical processes, tools, and templates from Jaime Fitzgerald, a leading analytics authority Includes process guides and electronic templates that are ideal for any size, sector, or geography of an organization Provides insight into the latest analytics methods used to understand customers, consumer behavior, and market opportunities.
List of contents
Preface: A crucial moment in the history of technology, data, and decision making
Section 1: A Framework to Convert Data to Dollars
1. Turning Data into Dollars using Analytics: Why It Matters More Than Ever 2. How did we get here? 3. Defining the challenges 4. A methodology to overcome the challenges 5. What does it take to apply the methodology? 6. Case Studies
Section 2: Putting the Data to Dollars Methodology into Practice
7. The Data to DollarsT Value Chain Methodology 8. Opportunity Identification 9. Insight + Analysis Requirements 10. Data Requirements 11. Defining the Required People, Processes and Technologies 12. Project Planning 13. Executing Analysis 14. Using the Output of Analysis 15. Onward and Upward: Growing Your Return on Data Analytics
Appendix
