A data warehouse is an organized collection of structured data that is used for applications such as reporting, analytics, or business intelligence. Traditional, on-premise data warehouses are still maintained by hospitals, universities, and large corporations, but these are expensive and space-consuming by today’s standards. Instead, data warehouse solutions like Google BigQuery and Amazon Redshift are allowing organizations of all sizes to benefit from the scalability and cost-effectiveness of cloud computing.
Data warehouses are important to learn about because they enable organizations to make data-driven decisions that can inform daily operations as well as future strategic initiatives. Analysts can use the data integration and extraction, transformation, loading (ETL) capabilities of business intelligence software like Pentaho to query and present information visually for maximum impact.
Working with diverse big data sets may require the use of a data lake, which is similar to a data warehouse but can take in all types of data - structured, unstructured, and raw. With software like Apache Hive, data scientists can sort and analyze data delivered by data lake solutions like Amazon S3 and Microsoft Azure to generate the real-time and predictive insights big data can provide.