www.codaten.de/2023/06/12/what-is-data-warehousing

Data warehousing is the consolidation and preparation of data to be used in workflows for decision-making. It also involves implementing advanced algorithms and analytics to analyze the data for business advantages. It can help reduce operational costs and improve decision-making.

It will improve the availability of data insights by reducing the time and effort involved in creating reports and obtaining meaningful information from different sources. It can simplify business operations, improve business intelligence and analytics, and machine-learning processes. It can also assist organizations reduce data silos and provide consistent views across all business data.

How you incorporate your data into a warehouse is vital to how efficient it will be. Organizations usually use an extract-transform-load (ETL) process to ingest data from different operational systems into a lakehouse. This allows them to choose the appropriate tools and architecture for their particular needs and objectives.

The Right Tools to Use for Architecture

Evaluating different data warehouse tools and architectures can help determine which one is best for your company. There are two main options, the Inmon and Kimball architectural models. Each has its own strengths and weaknesses. You’ll get the most from your data warehouse implementation when you choose the best tools and design that is appropriate for your business.

It’s also important to consider how often you’ll need add data to your warehouse. Depending on your needs you might need to ingest data continually since transaction processing happens or you may require it to be updated every few months. The frequency of data updates will help you plan and budget your data warehouse more efficiently.