The famous author of several Data Warehouse books, William H. Inmon first coined the concept of Data Warehouse (DW) in 1990. Inmon defined data warehouse as ‘a subject-oriented, integrated, time-variant and non-volatile collection of data.’ Extremely useful for Data Analysts, this data helps them to take business decisions and other data-related decisions in the organization.
For instance, in the world of E-commerce, a data warehouse includes and maintains data about products, costumer’s login credentials, addresses, buying behavior details, checkout details and other technical and non-technical information. In a warehouse, all the information is combined and consolidated in different tables such that companies can extract and analyze that data in an integrated manner.
Over the years, many applications have been designed to store huge datasets. A data warehouse is specially designed to perform business intelligence activities and enable professionals and employees to comprehend and improve the organization’s overall performance.
The two major functions of a data warehouse are:
It provides the multidimensional view of consolidated data in a warehouse. Additionally, the data warehouse environment supports ETL (Extraction, Transform and Load) solutions, data mining capabilities, statistical analysis, reporting and Online Analytical Processing (OLAP) Tools, which help in interactive and efficient data analysis in a multifaceted view.
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It is important to note that the DW operates with data extracted from multiple sources- internally built systems, third-party business groups, purchased applications and others. Many operations like production, transactions, sales and marketing, human resourcing are included from these source locations. With the buzz of big data and E-commerce, DW involves dealing with terabytes and petabytes of consumers and products data generated from each website click.
What happens next once all data is stored and arranged in databases? Here comes the term ‘data mining’ into action. It is the process of analyzing data to produce meaningful information and provide answers to the queries asked. Data mining uses various analytic tools to create summary reports, which are helpful in taking business decisions. The use of data mining in business applications leads to Business Analytics and Business Intelligence.
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Key Features of DW
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