Data and Analytics Strategy for Business
Kogan Page Ltd (Verlag)
978-1-3986-2201-2 (ISBN)
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Data presents a tremendous opportunity for businesses to increase revenue, reduce costs, mitigate risks, and improve customer satisfaction. An effective data strategy leveraging AI allows businesses to take advantage of the data they have.
Data and Analytics Strategy for Business is a practical guide for senior data leaders building a strategy for their organization. Starting with identifying the kind of data projects that reflect their company's goals and mission, it explains in detail how leaders can get buy-in for these projects from the rest of the organization. With emphasis on sourcing and identifying quality data, reporting and developing dashboards, using AI, understanding ethical considerations and better serving customers, 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, Transport for London and Bupa, this book is a step-by-step guide to designing and implementing a results-driven data strategy.
Simon Asplen-Taylor is the founder and CEO of DataTick, a leading data, analytics and AI consultancy and was the first Chief Data Officer in the UK. He previously served as Chief Data Officer for multiple FTSE firms including Bupa, UBS, Tesco and Regus and led some of the largest data led transformations in Europe. He is a Fellow of the Royal Statistical Society (RSS) and serves on the RSS's AI Taskforce. He In 2023, he was named by CEO Magazine as Most Influential Data Analytics CEO. He is based in London, UK.
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: A team game;
Section - PART TWO: Wave 1 - Aspire;
Chapter - 05: A quick win;
Chapter - 06: Repeat and learn;
Section - PART THREE: Wave 2 - Mature;
Chapter - 07: Data governance;
Chapter - 08: Data quality;
Chapter - 09: A single customer view;
Chapter - 10: Reports and dashboards;
Chapter - 11: Data risk management and ethics;
Section - PART FOUR: Wave 3 - Industrialize;
Chapter - 12: Automation, automation, automation;
Chapter - 13: Scaling up and scaling out;
Chapter - 14: Optimizing;
Section - PART FIVE: Wave 4 - Realize;
Chapter - 15: The voice of the customer;
Chapter - 16: Maximizing data science;
Chapter - 17: Sharing data with suppliers and customers;
Section - PART SIX: Wave 5 - Differentiate;
Chapter - 18: Data products;
Chapter - 19: Right leadership, right time;
Chapter - 20: Epilogue - Data success
| Erscheint lt. Verlag | 3.8.2025 |
|---|---|
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Sachbuch/Ratgeber ► Beruf / Finanzen / Recht / Wirtschaft ► Wirtschaft |
| Informatik ► Datenbanken ► Data Warehouse / Data Mining | |
| Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management | |
| Schlagworte | Automation • Business Strategy • data analytics • data culture, AI • data governance • Data Mining • Data Quality • Data strategy • machine learning |
| ISBN-10 | 1-3986-2201-X / 139862201X |
| ISBN-13 | 978-1-3986-2201-2 / 9781398622012 |
| Zustand | Neuware |
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