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Data Strategy – How to Profit from a World of Big Data, Analytics and Artificial Intelligence

Jezik EngleskiEngleski
Knjiga Meki uvez
Knjiga Data Strategy – How to Profit from a World of Big Data, Analytics and Artificial Intelligence Bernard Marr
Libristo kod: 45720305
Nakladnici Kogan Page, rujan 2025
Every business needs data to survive. Build and implement a strategy to take advantage of data and g... Cijeli opis
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Every business needs data to survive. Build and implement a strategy to take advantage of data and generate critical insights with renowned data expert and one of the world's leading voices in business Bernard Marr.

Data Strategy is the key to building a robust approach to data that will give business leaders the competitive advantage they need to succeed in the digital economy. From small organizations to huge multinationals, a data-driven strategy gives every organization the tools to revolutionize their uses of data to deliver impact and profits. By building the right strategy to collect, use and manage data, this book will prepare any organization for the data-driven future.

In its fully updated third edition, this bestselling title covers the latest advances in data and AI. With updates covering synthetic data, generative AI, the potential of quantum computing and expanded content on cybersecurity, regulations and ethics, this book shows how to craft your own strategy. Bernard Marr uses his unrivalled expertise to show how you can gain an edge in the rapidly changing data-driven world.

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Informacije o knjizi

Puni naziv Data Strategy – How to Profit from a World of Big Data, Analytics and Artificial Intelligence
Autor Bernard Marr
Jezik Engleski
Uvez Knjiga - Meki uvez
Datum izdanja 2025
Broj stranica 288
EAN 9781398619593
ISBN 1398619590
Libristo kod 45720305
Nakladnici Kogan Page
Težina 666
Dimenzije 156 x 234 x 15

Kategorija

Economics, Finance, Business & Management > Business & Management > Management & management techniques > Management decision making
Economics, Finance, Business & Management > Business & Management > Business strategy
Computing & Information Technology > Databases > Data mining
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