There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial. Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to extract valuable insights from their data. Facilitating a clear understanding of big data, it supplies authoritative insights from expert contributors into leveraging data resources, including big data, to improve decision making. Illustrating basic approaches of business intelligence to the more complex methods of data and text mining, the book guides readers through the process of extracting valuable knowledge from the varieties of data currently being generated in the brick and mortar and internet environments. It considers the broad spectrum of analytics approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining.
 <ul>
 <li>Includes a foreword by Thomas H. Davenport, Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for Analytics</li>
 <li>Introduces text mining and the transforming of unstructured data into useful information</li>
 <li>Examines real time wireless medical data acquisition for today’s healthcare and data mining challenges</li>
 <li>Presents the contributions of big data experts from academia and industry, including SAS</li>
 <li>Highlights the most exciting emerging technologies for big data―Hadoop is just the beginning</li>
 
</ul>
 Filled with examples that illustrate the value of analytics throughout, the book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes. It also provides in-depth coverage of analyzing unstructured data with text mining methods to supply you with the well-rounded understanding required to leve

Big Data, Mining, and Analytics: Components of Strategic Decision Making

Computers & Technology

Kudyba, Stephan

Computer Science

Auerbach Publications

There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial. Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to extract valuable insights from their data. Facilitating a clear understanding of big data, it supplies authoritative insights from expert contributors into leveraging data resources, including big data, to improve decision making. Illustrating basic approaches of business intelligence to the more complex methods of data and text mining, the book guides readers through the process of extracting valuable knowledge from the varieties of data currently being generated in the brick and mortar and internet environments. It considers the broad spectrum of analytics approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining. <ul>
<li>Includes a foreword by Thomas H. Davenport, Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for Analytics</li> <li>Introduces text mining and the transforming of unstructured data into useful information</li> <li>Examines real time wireless medical data acquisition for today’s healthcare and data mining challenges</li> <li>Presents the contributions of big data experts from academia and industry, including SAS</li> <li>Highlights the most exciting emerging technologies for big data</li>
</ul>
Filled with examples that illustrate the value of analytics throughout, the book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes. It also provides in-depth coverage of analyzing unstructured data with text mining methods.

Business & Money

Management & Leadership

The authors bring a dual perspective―that of a practicing consultant and that of a professor of economics―to the complex strategic questions facing managers and corporate leaders who want their firms to get the most out of their investments in information technology. The information economy is built upon the myriad and sometimes unforeseen ways in which information technologies have become engines of productivity in themselves, rather than just fancy adjuncts. In explaining the rise of the information economy, the authors provide not only valuable context often missing from today's discussions but also a thorough understanding of the origination, development, and diffusion process of innovations. They also examine prevailing practices and implications for the future, including the potential pitfalls common to some information technology strategies.
Relying on an underpinning of economic theory combined with heavy empirical analysis, Kudyba and Diwan describe the true nature of the information economy, paying as much attention to its particularities as to its more profound implications. How is information technology being implemented across industry sectors, and how can it be harnessed to improve overall firm-level productivity? How have innovations in high technology impacted e-commerce? Which e-commerce strategies prevail, and what can be expected of them? How can traditional economic theory help managers evaluate such in-vogue strategies as customer relationship management, market exchanges, and supply chain management? The authors answer these questions and more, including one of the most vexing in the short history of e-commerce: What led to the demise of so many technology stocks and dot-coms following the spring 2000 Nasdaq plunge, and what are the longer-term prospects for e-business?

Information Technology, Corporate Productivity, and the New Economy

Economics

Praeger

Managing Data Mining: Advice from Experts is a collection of leading business applications in the data mining and multivariate modeling spectrum provided by experts in the field at leading US corporations. Each contributor provides valued insights as to the importance quantitative modeling provides in helping their corresponding organizations manage risk, increase productivity and drive profits in the market in which they operate. Additionally, the expert contributors address other important areas which are involved in the utilization of data mining and multivariate modeling that include various aspects in the data management spectrum (e.g. data collection, cleansing and general organization). (This book is a release under the IT Solution Series.) Foreword by Dr. Jim Goodnight, SAS, Inc., USA Selected contributions from: Citigroup Blue Cross Blue Shield Chubb Insurance American Healthways Nielsen//NetRatings

Managing Data Mining: Advice from Experts (IT Solutions series)

Software

Cybertech Publishing

Data Mining and Business Intelligence: A Guide to Productivity

An overview of data mining technology and how it is applied in a business environment. Methodologies are described that solve a variety of business problems and enhance firm-level efficiency in a less technical, managerial style. The book also incorporates the data mining process into the spectrum of complementary technologies that together comprise corporate information systems that promote business intelligence. Business intelligence involves the proliferation of value-added information throughout a given enterprise through the use of various software applications that promote efficiency for the firm.

Hoptroff, Richard

IGI Global

See the best price to sell, buy, or rent books by Kudyba, Stephan. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Kudyba, Stephan

See the best price to sell, buy, or rent books by Kudyba, Stephan. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Big Data, Mining, and Analytics: Components of Strategic Decision Making

Big Data, Mining, and Analytics: Components of Strategic Decision Making

Information Technology, Corporate Productivity, and the New Economy

Managing Data Mining: Advice from Experts (IT Solutions series)

Data Mining and Business Intelligence: A Guide to Productivity