Normalization

Normalization in business intelligence and data analytics is a technique used to organize data in a database. Think about it like cleaning up a messy room so you can find things more easily; normalization puts data into tables and columns in a way that reduces redundancy (repeating the same data) and dependency (how much bits of data rely on each other). By doing this, data becomes more streamlined and efficient to use.

This process is crucial because it helps prevent errors and simplifies the management of the data. When a database is normalized, changes in one spot, like updating a customer’s address, only need to be made once, rather than searching for and fixing every instance where the address appears. It also helps in making querying data faster and less complicated, which is especially important when dealing with large databases.

For businesses, having a well-organized database is important not just for everyday operations, but also for making sure that their analyses are accurate and useful. Normalization makes databases logically orderly and reduces the risk of errors, ensuring that reports, dashboards, and other analytical tools reflect the true picture of the business’s activities.