Data Warehousing Fundamentals
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A system used for reporting and data analysis is referred to as a data warehouse. It is considered an essential component of business intelligence. Integrated historical and current data from multiple sources are stored within it. Data can be categorized based on factors such as temporal variance, volatility, integration method, subject focus, granularity, and more. Subsequently, the data is organized into groups, individual facts, and aggregated facts. The data sources undergo cleansing, cataloging, and transformation before being utilized for data mining, market research, decision support, a...
A system used for reporting and data analysis is referred to as a data warehouse. It is considered an essential component of business intelligence. Integrated historical and current data from multiple sources are stored within it. Data can be categorized based on factors such as temporal variance, volatility, integration method, subject focus, granularity, and more. Subsequently, the data is organized into groups, individual facts, and aggregated facts. The data sources undergo cleansing, cataloging, and transformation before being utilized for data mining, market research, decision support, and online analytical processing. Analyzing, retrieving, transforming, loading, and extracting data, along with managing the data dictionary, are crucial elements of a data warehousing system. Data warehouses can be structured using bottom-up, top-down, or hybrid design models. This book presents the complex subject of data warehousing in the most comprehensible and easy to understand language. The various sub-fields of data warehousing along with technological progress that have future implications are glanced at herein. This book will serve as a valuable source of reference for those interested in this field.
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