Online data warehouses are designed to store information in a permanent system that is accessible to all employees who require information for making decisions. They also provide a historical archive of data, and serve as an unifying source of truth, so users can analyze data from different sources without relying on outdated information.
There are a myriad of factors to take into consideration when choosing the appropriate architecture, platforms and tools for Data Warehouses. For example is it better to have the warehouse deployed on-premises or cloud-based? Should it employ extract transform and load (ETL) or direct-to-database integration methods? How often should data be refreshed? What change data capture capabilities be used to capture updates and feed them into the warehouse? The business use cases of the company will ultimately determine the selection of the best technology.
A bicycle manufacturer, for instance might use its data store to understand the current behavior of its customers. It could find that its customers are predominantly women over 50 years old, and would be keen to learn more about the retail outlets they prefer to shop at for bicycles. This information can aid the company in improving its marketing and development efforts.
Alternatively, an IT team could use its data warehouse to support the auditing process and regulatory compliance by efficiently supplying historical records to review. This could save an organization time and money by removing redundant data.
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