The goal of online data warehouses is to consolidate data in a stable, standardized system that is accessible to all relevant employees to assist in making decisions. They serve as an archive of data as well as a one source of truth, making it possible for users to evaluate data from various sources without having to rely on outdated data.
When it comes time to choose the right architecture, platform and tools for a data warehouse, there are plenty of factors to consider. For example is it better to have the warehouse built on-premises or cloud-based? Should it be using extract, transform and load (ETL) or direct-to-database integration methods? How often should data be refreshed? What is the process by which the change data capture capability be used to capture and feed updates to the warehouse? In the end, deciding on the right technologies should be based on the organization’s specific business needs.
For instance the bicycle manufacturer could make use of its data warehouse to discover more about the current customer behavior and trends. It might find that their customers are mostly women older than 50, and would be interested in finding out more about the stores they shop at for bicycles. This information could help the company improve its marketing and development strategies.
Alternatively an IT team could make use of its data warehouse to support the auditing and compliance processes by efficiently supplying historical records to be reviewed. This could acquisition life cycle model overview save a company time and money by removing redundant data.