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.