Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners (Wiley and SAS Business Series) - Hardcover

Über die Autorin bzw. den Autor

JARED DEAN is a Senior Director of Research and Development at SAS Institute. He is responsible for the development of SAS's worldwide data mining solutions. This includes customer engagements, new feature development, technical support, sales support, and product integration. Prior to joining SAS, Dean worked as a Mathematical Statistician for the US Census Bureau.

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In today's business environment an endless stream of big data often shapes critical decision-making processes. To maintain and sustain a profitable business, it is imperative to harness the power of big data. However, simply accessing the data and having the ability to process it isn't enough to yield meaningful results.

Big Data, Data Mining, and Machine Learning offers marketing executives, business leaders, and technology experts a comprehensive resource for developing and implementing the strategies and methods that can consistently produce effective results and ultimately increase profitability. In this book, Jared Dean offers an accessible and thorough review of the current state of big data analytics and the growing trend toward high performance computing architectures. Big Data, Data Mining, and Machine Learning clearly shows how big data analytics can be leveraged to foster positive change and drive efficiency.

Step by step, Jared Dean reveals what it takes to use technology to create an analytical environment for data mining, machine learning, and working with big data. The author also explores the trade-offs that result from certain technology choices. Big Data, Data Mining, and Machine Learning includes a range of algorithms and methods that can be implemented to glean information from mined data and provides explanations on how to apply these approaches most effectively. Filled with illustrative case studies, the book offers myriad examples of successful organizations that have used new technological advances and algorithms to their competitive advantage. The author also includes a discussion of explanatory and predictive modeling and how these tools can be applied to the decision-making process.

For any organization that wants to access the power of data analytics, this important book can serve as a linchpin for understanding the underlying technology and analysis of big data. Now you can take control of your organization's big data analytics with confidence and create results that go directly to the bottom line.

Aus dem Klappentext

In today's business environment an endless stream of big data often shapes critical decision-making processes. To maintain and sustain a profitable business, it is imperative to harness the power of big data. However, simply accessing the data and having the ability to process it isn't enough to yield meaningful results.

Big Data, Data Mining, and Machine Learning offers marketing executives, business leaders, and technology experts a comprehensive resource for developing and implementing the strategies and methods that can consistently produce effective results and ultimately increase profitability. In this book, Jared Dean offers an accessible and thorough review of the current state of big data analytics and the growing trend toward high performance computing architectures. Big Data, Data Mining, and Machine Learning clearly shows how big data analytics can be leveraged to foster positive change and drive efficiency.

Step by step, Jared Dean reveals what it takes to use technology to create an analytical environment for data mining, machine learning, and working with big data. The author also explores the trade-offs that result from certain technology choices. Big Data, Data Mining, and Machine Learning includes a range of algorithms and methods that can be implemented to glean information from mined data and provides explanations on how to apply these approaches most effectively. Filled with illustrative case studies, the book offers myriad examples of successful organizations that have used new technological advances and algorithms to their competitive advantage. The author also includes a discussion of explanatory and predictive modeling and how these tools can be applied to the decision-making process.

For any organization that wants to access the power of data analytics, this important book can serve as a linchpin for understanding the underlying technology and analysis of big data. Now you can take control of your organization's big data analytics with confidence and create results that go directly to the bottom line.