Data warehouse platforms are one of the most utilized type of Information Technology (IT)-related services of the majority of businesses nowadays regardless of the size of the business.

For three decades already, data warehousing has been a very important part of data infrastructure and architecture in the IT industry and has become a huge help for many organizations throughout the years, however, despite its heritage, there are still many confusions that surround this great innovative technological tool that is mainly designed to optimize business operation.

Because of the advent of data lakes, big data, and advanced analytics, some that came from the IT industry have raised questions whether data warehousing is still a relevant tool for today’s businesses and industries, and to end this kind of confusion, tech experts and business leaders have already eliminated the doubt that data warehousing is irrelevant at all. In this post, let us talk about the importance of data warehousing and how it helps a business regardless of its size.

Data warehousing is defined by the type of data that it stores, and the people that utilize it. It is designed for decision support and Business Intelligence activities. The data warehouse is separate from the daily online transaction processing applications that operate the core business, which thereby reduces the contention for both operation transactions and analytical queries of a business or an organization.

A data warehouse is usually a read-only, with the data organized based on the business’ or client’s requirements and needs rather than by computing processes. The data warehouse classifies information by subjects of interest of the business analysts, managers, as well as business leaders through the stored information and data from customers, products, and registered accounts that the business has during transactions. The data is loaded into the warehouse which is made available for query by the business users that are mentioned above.

The information that is stored in the data warehouse is based on the historical record that spans the transactions that have occurred over time. For this reason, the warehoused data is usually summarized or aggregated to make it easier for scanning, accessing, and querying while the redundant data is also included in the data warehouse to provide users with different viewing points of information that is both logical and easy to understand.

The information that data warehouses contain has been culled from operational systems, as well as other external data from third-party or point-of-sale information that is gathered from the business’ transactions and operations. The data that is warehoused is then consolidated and stored in a very consistent form for the entire business that will be formatted, stored, maintained, and used in different ways possible.

The data stored in the warehouse does not change at all, while the new data uploaded to it also remains the same, but the frequency of adding more data is based on the latency requirements of the Business Intelligence applications and other decision support systems that are also utilized by a business. A lot of new data warehouses are near-real-time in storing data, which means that there is a very low latency between the data and the production system every time there is a movement going to the data warehouse.