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A data warehouse is a repository of information that is used to store and analyze large amounts of data. It is an essential component in many organizations, as it helps them gain insights into their business operations and make more informed decisions. The job of a data warehouse is to provide reliable, consistent, accurate and timely access to the organization’s historical data—data that has been collected over time from multiple sources. In order for a data warehouse to be successful, it must have efficient processes in place for collecting, cleansing, transforming and loading (ETL) the raw source data into its target environment while maintaining high levels of accuracy. Once the source systems are integrated with the target system through ETL processes, the next step involves building out dimensional models such as star schemas or snowflake schemas so that queries can be executed against them quickly and effectively. This requires having strong knowledge of database design principles such as normalization techniques which help optimize query performance by eliminating redundant fields. Finally, once all these steps are completed successfully then reports/dashboards can be built using BI tools like Tableau or PowerBI so users can visualize their desired results in an easy-to-understand format. To summarize it up nicely – Data Warehouse professionals are responsible for extracting valuable insights from large datasets by designing efficient databases structures within well-managed environments while also delivering consistent user experiences on top via powerful visualizations & reporting capabilities