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Library Catalogues as Data

Research, Practice and Usage

Studies in English Language

Data-Intensive Investigations of English

Chandos Advances in Information Series

Challenges for Universities in a Post COVID World and How to Address Them

The Digital Student

Information use is changing rapidly in the digital age, leading to complex intellectual property and ownership issues. Exploring the ethical implications of this new environment, specifically as they relate to information professionals, this book offers guidance on making ethical choices.

Ethics, Information, and Technology

The School and Youth Librarians’ Intellectual Freedom Toolkit

Protecting Children’s Information Access

Discover the AI and data skills you'll need and develop your confidence to succeed in the digital age.

Gain the Confidence You Need to Succeed

Data and AI Skills

Inside Rugby's Tactical and Data Revolution

Attacking the Space

HBR's 10 Must Read

Data is your business. Have you unlocked its full potential?If you read nothing else on data strategy, read this book. We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you maximize your analytics capabilities; harness the power of data, algorithms, and AI; and gain competitive advantage in our hyperconnected world.This book will inspire you to: <ul><li>Reap the rewards of digital transformation</li><li>Make better data-driven decisions</li><li>Design breakout products that generate profitable insights</li><li>Address vulnerabilities to cyberattacks and data breaches</li><li>Reskill your workforce and build a culture of continuous learning</li><li>Win with personalized customer experiences at scale</li></ul>This collection of articles includes "What's Your Data Strategy?," by Leandro DalleMule and Thomas H. Davenport; "Democratizing Transformation," by Marco Iansiti and Satya Nadella; "Why Companies Should Consolidate Tech Roles in the C-Suite," by Thomas H. Davenport, John Spens, and Saurabh Gupta; "Developing a Digital Mindset," by Tsedal Neeley and Paul Leonardi; "What Does It Actually Take to Build a Data-Driven Culture?," by Mai B. AlOwaish and Thomas C. Redman; "When Data Creates Competitive Advantage," by Andrei Hagiu and Julian Wright; "Building an Insights Engine," by Frank van den Driest, Stan Sthanunathan, and Keith Weed; "Personalization Done Right," by Mark Abraham and David C. Edelman; "Ensure High-Quality Data Powers Your AI," by Thomas C. Redman; "The Ethics of Managing People's Data," by Michael Segalla and Dominique Rouzies; "Where Data-Driven Decision-Making Can Go Wrong," by Michael Luca and Amy C. Edmondson; "Sizing Up Your Cyberrisks," by Thomas J. Parenty and Jack J. Domet; "A Better Way to Put Your Data to Work," Veeral Desai, Tim Fountaine, and Kayvaun Rowshankish; and "Heavy Machinery Meets AI," by Vijay Govindarajan and Venkat Venkatraman.HBR's 10 Must Reads are definitive collections of classic ideas, practical advice, and essential thinking from the pages of Harvard Business Review. Exploring topics like disruptive innovation, emotional intelligence, and new technology in our ever-evolving world, these books empower any leader to make bold decisions and inspire others.

HBR's 10 Must Reads on Data Strategy

Research Methods for Library, Archives, and Museum Professionals

Knowledge into Action

How to Design, Deploy, and Sustain an Effective Data Governance Program

Data Governance

"Tools from macroeconomics and finance to incorporate the central role that data plays in the economy. The most valuable firms in the global economy are valued largely for their data. Amazon, Apple, Google, and others have proven the competitive advantage of a good data set. And yet despite the growing importance of data as a strategic asset, modern economic theory neglects its role. In this book, Isaac Baley and Laura Veldkamp draw on a range of theoretical frameworks at the research frontier in macroeconomics and finance to model and measure data economies. Starting from the premise that data is digitized information that facilitates prediction and reduces uncertainty, Baley and Veldkamp uncover the ways that firm-level data choices resonate throughout the broader macroeconomic and financial landscapes.With The Data Economy, Baley and Veldkamp put forward a broad research agenda with a formal yet accessible approach, offering an analysis of the data economy and its welfare effects that will be of interest to practitioners, researchers, and graduate students. The tools presented, many of them information-related methods from macroeconomics and finance, are theoretical but introduced with careful attention to how they can inform or enable measurement. Applications include assessing the economic worth of data and unraveling its influence on the structure of production, inflation, and pricing dynamics; firm and investor behavior; advertising; market power; and asset pricing. Baley and Veldkamp bring readers to the cutting edge of this novel research area, equipping them to formulate their own theoretical advances and policy analysis"--

Tools from macroeconomics and finance to incorporate the central role that data plays in the economy The most valuable firms in the global economy are valued largely for their data. Amazon, Apple, Google, and others have proven the competitive advantage of a good data set. And yet despite the growing importance of data as a strategic asset, modern economic theory neglects its role. In this book, Isaac Baley and Laura Veldkamp draw on a range of theoretical frameworks at the research frontier in macroeconomics and finance to model and measure data economies. Starting from the premise that data is digitized information that facilitates prediction and reduces uncertainty, Baley and Veldkamp uncover the ways that firm-level data choices resonate throughout the broader macroeconomic and financial landscapes. With The Data Economy, Baley and Veldkamp put forward a broad research agenda with a formal yet accessible approach, offering an analysis of the data economy and its welfare effects that will be of interest to practitioners, researchers, and graduate students. The tools presented, many of them information-related methods from macroeconomics and finance, are theoretical but introduced with careful attention to how they can inform or enable measurement. Applications include assessing the economic worth of data and unraveling its influence on the structure of production, inflation, and pricing dynamics; firm and investor behavior; advertising; market power; and asset pricing. Baley and Veldkamp bring readers to the cutting edge of this novel research area, equipping them to formulate their own theoretical advances and policy analysis.

Tools and Applications

The Data Economy

Mathematical Modelling for Big Data Analytics is a comprehensive guidebook that explores the use of mathematical models and algorithms for analyzing large and complex datasets. The book covers a range of topics, including statistical modeling, machine learning, optimization techniques, and data visualization, and provides practical examples and case studies to demonstrate their applications in real-world scenarios. Users will find a clear and accessible resource to enhance their skills in mathematical modeling and data analysis for big data analytics. Real-world examples and case studies demonstrate how to approach and solve complex data analysis problems using mathematical modeling techniques. This book will help readers understand how to translate mathematical models and algorithms into practical solutions for real-world problems. Coverage of the theoretical foundations of big data analytics, including qualitative and quantitative analytics techniques, digital twins, machine learning, deep learning, optimization, and visualization techniques make this a must have resource.

Mathematical Modeling for Big Data Analytics

Cut through the hype with this essential guide for any business professional looking to improve their organization's efficiency through technology.

Use Technology to Improve Your Business

The Practical Guide to Digital Transformation

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