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Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners (Wiley and SAS Business Series), by Jar
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With big data analytics comes big insights into profitability
Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency.
With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes:
- A complete overview of big data and its notable characteristics
- Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases
- Comprehensive coverage of data mining, text analytics, and machine learning algorithms
- A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes
Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
- Sales Rank: #856918 in Books
- Published on: 2014-05-27
- Original language: English
- Number of items: 1
- Dimensions: 9.30" h x 1.00" w x 6.30" l, 1.05 pounds
- Binding: Hardcover
- 265 pages
Review
explains what it covers very well (ZDNet, September 2014)
From the Inside Flap
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.
From the Back Cover
Praise for Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners
“We needed this book, an efficient tour guide through the methods and tools of predictive modeling by an expert in the field. There are lots of books that are collections of journalistic success stories in business analytics. There are lots of books that go into the methods of predictive analytics in math-speak. Here we have the high-level tour, but with enough description to understand the guts of each method.”
—John Sall, Executive Vice President, SAS Institute
“Jared Dean provides an interesting and approachable perspective on one of today’s most discussed topics: using big data and analytics to create value for organizations. The combination of simple examples and deep insights make this a vital read for managers who need to have a complete picture of the analytical process and the great potential it unlocks.”
—Chris Bingham, Philip Hettleman Scholar and Associate Professor of Strategy & Entrepreneurship, The University of North Carolina at Chapel Hill
“This book provides excellent coverage of the technical skills needed by analytical consultants in today’s market. The focus on modern methods makes this book relevant for business leaders who want to reap the rewards that analytics can bring to an organization. In my experience, one of the greatest missing links in implementing an analytics-based strategy is a shortage of executives who truly understand analytics—both the capabilities analytics can provide as well as the limitations. This book can help you close that knowledge gap. Jared does an excellent job of making the concepts approachable while giving complete explanations with ample examples.”
—Mark Pitts, MS, MAcc, Vice President, Enterprise Informatics & Data Analytics, Highmark Health
“A wonderful treatise that cuts through the noise about big data and lays out clearly what it is, how it can be integrated with data analytic models, and how companies can leverage it to add value to their business. I am confident this book will be a must read for anyone trying to make sense of how to convert big data into actionable insights for their organization.”
—Dr. Goutam Chakraborty, Professor (Marketing) and Director of Graduate Certificate in Business Data Mining, Oklahoma State University
Most helpful customer reviews
0 of 0 people found the following review helpful.
Four Stars
By Kattamuri S. Sarma
Good refeence
2 of 2 people found the following review helpful.
by far was the most educating and beneficial book in the field to me
By Rayan Hafiz
For the past few months I bought many books in the field of Business Analytics, data mining, and big data. This one by far was the most educating and beneficial to my learning. It has very smooth language, very well written and organized and most importantly it explains the basic methods and concepts in data mining in a simple and easily understandable way with great introductional history on big data. I attended a presentation by the author few weeks back summarizing some ideas from the book and man I'm a fan. I told myself I wish if this guy was my instructor in collage as he is very good in delivering those not so easy concepts. Highly recommended if you really want to learn about data mining and big data.
6 of 8 people found the following review helpful.
Well structured and easy to read, light on math
By Amazon Customer
This is a well structured and easy to read book. As the title says, it discusses big data, data mining and machine learning and the potential value added to the business. The technical side, however, is light. There aren't many equations in the text and presented machine learning topics are rather high level. Overall, non-technical audience and lightly technical managers would benefit from the book, but those looking for heavy math and hands on data science should look elsewhere.
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