Data warehousing refers to the practice of collecting, storing and analyzing large volumes of business information for use in decision making. It provides one source of truth across multiple forms of data so users can make informed business decisions without jeopardizing its integrity.
Data Warehouse Definition: A data warehouse is an array of relational databases used to store, organize and analyze large volumes of data. These sets may then be utilized by organizations for supporting decision making activities like forecasting product performance or developing promotional strategies.
Integration Database: At the heart of any data warehouse lies an integrated database storing transactional, operational and line-of-business information as well as historical details. Typically this data can span hundreds of gigabytes or even petabytes in size!
Subject Oriented Data Warehouses: By categorizing data warehouses according to subject matter such as sales, they offer companies the potential to quickly answer important business questions quickly and efficiently as well as reduce implementation and maintenance time and costs.
Integration: A data warehouse must be capable of unifying information from various sources into one cohesive format, solving issues like name conflicts and unit of measure inconsistencies, while handling duplicated data sets effectively. To accomplish this goal, data warehousing typically uses ETL tools for extracting and transforms as well as metadata management as well as archiving and baking up techniques to accomplish its goals.
Data warehousing has rapidly become an indispensable component of business intelligence, helping organizations make quality business decisions and generate significant revenues, while simultaneously strengthening their market presence through systematic, contextual data collection.