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Full Description
Data and AI present a tremendous opportunity to improve business performance by increasing operational efficiency, revenues and customer satisfaction. An effective data strategy leveraging the power of AI allows businesses to create a competitive advantage.
Data and Analytics Strategy for Business is a practical guide for business, technology and data leaders building a data, analytics and AI strategy for their organization. Starting by identifying the value you can obtain from data, analytics and AI, this book shows you how to maximise that value to support your organization's goals and mission. It covers the importance of having high quality data to generate trust, getting the whole organization on board as well as all the other essential elements required to complete your strategy. This book provides the keys to using data to drive improved business results.
Incorporating the latest developments in AI, this new edition of Data and Analytics Strategy for Business shows how leaders can use AI right away to get value from their existing strategy. It provides practical guidance and recommendations for implementing AI and machine learning to maximize performance. Filled with real-world examples from organizations including Tesco and Facebook, this book is a step-by-step guide to designing and implementing a results-driven data strategy.
Contents
Section - PART ONE: How data and analytics can help you grow your business;
Chapter - 01: How can this book help you?;
Chapter - 02: The business case for data;
Chapter - 03: Your data and analytics strategy;
Chapter - 04: AI Strategy
Chapter - 05: A team game;
Section - PART TWO: Wave 1 - Aspire;
Chapter - 06: A quick win;
Chapter - 07: Repeat and learn;
Section - PART THREE: Wave 2 - Mature;
Chapter - 08: Data governance;
Chapter - 09: Data quality;
Chapter - 10: Single Customer View (SCV);
Chapter - 11: Generating insights;
Chapter - 12: Data risk management and ethics;
Section - PART FOUR: Wave 3 - Industrialize;
Chapter - 13: Automation, automation, automation;
Chapter - 14: Scaling up and scaling out;
Chapter - 15: Data and AI culture;
Section - PART FIVE: Wave 4 - Realize;
Chapter - 16: The voice of the customer;
Chapter - 17: Maximizing data science and AI;
Chapter - 18: Sharing data with suppliers and customers;
Section - PART SIX: Wave 5 - Differentiate;
Chapter - 19: Data products;
Chapter - 20: Right leadership, right time;
Chapter - 21: Epilogue - Data success
