Elliott Masie

Big Learning Data (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Welcome to the big data revolution. In today's wired world, we interact with millions of pieces of information every day. Capturing that information and making sense of it is the revolutionary impact of big data on business-and on learning.

Thought leader Elliott Masie and Learning CONSORTIUM Members bring a powerful new book to the T&D profession. They provide a SWOT analysis of big data and implications for learning and development professionals.

Big learning data is at your fingertips. You need to know why it matters.

Find out where to start with big learning data.

Think differently about the data you have.

Understand transparency, user sensitivity, and who owns "my" big data.

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Produktdetails

• Verlag: Association for Talent Development
• Seitenzahl: 160
• Erscheinungstermin: 27. November 2013
• Englisch
• ISBN-13: 9781607286479
• Artikelnr.: 67250770

Autorenporträt

Elliott Masie is a provocative, engaging, and entertaining futurist, analyst, and speaker. He enjoys topics related to learning, technology, data, and workplace performance. Elliott has varied feelings about big data; he is simultaneously intrigued, challenged, excited, and concerned about how big data will be experienced by employees, citizens, and organizations. He is the editor of Learning TRENDS by Elliott Masie, an Internet newsletter read by more than 52,000 business executives worldwide, and is a regular columnist in several publications. He hosts an annual learning conference each fall, bringing together thousands of learning professionals to benchmark and collaborate on the rapidly changing world of learning and workplace performance.For almost four decades, Elliott's focus has been the evolution of learning, including the use of technology for knowledge, learning, and collaboration throughout organizations. He is acknowledged as the first analyst to use the term e-learning in the 1990s, and he has been on the forefront of social, mobile, and video-based learning experiments.