02722cam a2200385 i 4500 23228178 US-DLC 20251102105619.0 230714s2024 nyu b 001 0 eng 2023024328 9780231206860 (hardback) 9780231556699 (ebook) 23228178 au eng rda DLC au pcc Alfaisal Main Library HD30.215 .F74 2024 Freidman, Howard Steven, author. Winning with data science : a handbook for business leaders / Howard Steven Freidman and Akshay Swaminathan. 2024 New York : Columbia Business School Publishing, [2024] x, 259 pages ; 23 cm text txt rdacontent unmediated n rdamedia volume nc rdacarrier Includes bibliographical references and index. Tools of the Trade -- The Data Science Project -- Data Science Foundations -- Making Decisions with Data -- Clustering, Segmenting, and Cutting Through the Noise -- Building Your First Model -- Tools for Machine Learning -- Pulling It Together -- Ethics. "Data science is increasingly important in the business world, not just for the teams in charge of implementing it but the professionals adjacent to them. Yet not all businesspeople have a general understanding of the basics-and if senior management assigns them to work alongside a data science team, they'll need that knowledge as soon as possible without having to take online courses or dive down the Internet rabbit hole. This book provides that knowledge base, walking readers through the key ideas needed to communicate and work with a data science team. They will be able to understand the basic technical lingo, recognize the types of talent on the team and pose good questions to your data scientists to open up more insights, create opportunities, and generate value. By the end of the book they will be able to answer key questions including how data is collected and stored, what hardware and software tools are needed to analyze data, who does what on the data science team and which models should be considered for specific projects. Most critically, they will also be armed with critical questions that you can use to further probe data analysts, statisticians, data scientists and other technical experts to better understand the value of their work for a business"-- Management Statistical methods. Databases. Data mining. Electronic data processing. Print books. local 4 lcc BOOKS 607766 607766 0 0 lcc 0 0 AU AU GEN 2025-11-02 0 HD30.215 .F74 2024 AU00000000020649 2025-11-02 10:57:38 200.00 2025-11-02 BOOKS