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Data Warehousing OLAP and Data Mining

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This book is intended for Information Technology (IT) professionals who have been hearing about or have been tasked to evaluate, learn or implement data warehousing technologies. This book also aims at providing fundamental techniques of KDD and Data Mining as well as issues in practical use of Mining tools.

Far from being just a passing fad, data warehousing technology has grown much in scale and reputation in the past few years, as evidenced by the increasing number of products, vendors, organizations, and yes, even books, devoted to the subject. Enterprises that have successfully implemented data warehouses find it strategic and often wonder how they ever managed to survive without it in the past. Also Knowledge Discovery and Data Mining (KDD) has emerged as a rapidly growing interdisciplinary field that merges together databases, statistics, machine learning and related areas in order to extract valuable information and knowledge in large volumes of data.

Volume-I is intended for IT professionals, who have been tasked with planning, managing, designing, implementing, supporting, maintaining and analyzing the organization’s data warehouse.

The first section introduces the Enterprise Architecture and Data Warehouse concepts, the basis of the reasons for writing this book.

The second section focuses on three of the key People in any data warehousing initiative: the Project Sponsor, the CIO, and the Project Manager. This section is devoted to addressing the primary concerns of these individuals.

The third section presents a Process for planning and implementing a data warehouse and provides guidelines that will prove extremely helpful for both first-time and experienced warehouse developers.

The fourth section focuses on the Technology aspect of data warehousing. It lends order to the dizzying array of technology components that you may use to build your data warehouse. The fifth section opens a window to the future of data warehousing.

The sixth section deals with On-Line Analytical Processing (OLAP), by providing different features to select the tools from different vendors.

Volume-II shows how to achieve success in understanding and exploiting large databases by uncovering valuable information hidden in data; learn what data has real meaning and what data simply takes up space; examining which data methods and tools are most effective for the practical needs; and how to analyze and evaluate obtained results.
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