Data Warehousing OLAP and Data Mining

S. Nagabhushana "Data Warehousing OLAP and Data Mining"
New Age International | English | | ISBN: N/A; EAN: 9788122417647 | 350 pages | PDF | 1,7 MB

This book is mainly intended for IT students and professionals to learn or implement data warehousing technologies. It experiences the real-time environment and promotes planning, managing, designing, implementing, supporting, maintaining and analyzing data warehouse in organizations and it also provides various mining techniques as well as issues in practical use of Data Mining Tools.

The book is designed for the target audience such as specialists, trainers and IT users. It does not assume any special knowledge as background. Understanding of computer use, databases and statistics will be helpful.
About the Author(s):
Nagabushna Sujihal was born at Bellary in the year 1982 and completed his primary education at National School, Bangalore. He had his Engineering graduation in Electronic and Communication Engineering from Bellary Engineering College, affiliated to Visveswaraih Technological University, Belgaum, Karnataka in the year 2003. Soon after his degree in Engineering, he joined teaching profession at Intell Engineering College, Anantpur, Andhra Pradesh. At present, he is perceiving his post-graduation at Sathayabhama Deemed University, Chennai in Computer Science Engineering.

Contents:
VOLUME I: DATA WAREHOUSING IMPLEMENTATION AND OLAP

PART I: INTRODUCTION The Enterprise IT Architecture
Data Warehouse Concepts
PART II: PEOPLE The Project Sponsor
The CIO
The Project Manager
PART III: PROCESS Warehousing Strategy
Warehouse Management and Support Processes
Data Warehouse Planning
Data Warehouse Implementation
PART IV: TECHNOLOGY Hardware and Operating Systems
Warehousing Software
Warehouse Schema Design
Warehouse Metadata
Warehousing Applications
PART V: MAINTENANCE, EVOLUTION AND TRENDS Warehouse Maintenance and Evolution
Warehousing Trends
PART VI: ON-LINE ANALYTICAL PROCESSING Introduction
OLAP Application
VOLUME II: DATA MINING Introduction
Data Mining with Decision Trees
Data Mining with Association Rules
Automatic Clustering Detection
Data Mining with Neural Network

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