What Is Data Enrichment?

If you don't know or have been living under a rock, you must understand that data is the new oil. This common phrase in today's business world makes much sense. Data is valuable to almost any enterprise. It can be used to make more informed decisions, understand customers better, and optimize processes. If you have data, you have power. While businesses are rapidly realizing this and making data-driven decisions a part of their everyday workflow, one thing needs to be addressed: enriching data before using it. Data enrichment is a general term that refers to processes used to enhance or refine raw data to make it more useful for various purposes, for example, by adding additional metadata or even making sense of unstructured information (like texts). It is the process of adding missing information to existing data. It can be used to correct errors in a database, or it can be used to provide information that was not present initially. For example, data enrichment is often used to fill out the information about a person's age or birthday. It can also be used to correct misspellings or typographical errors in the data (e.g., "Mississippi" becomes "Mississippi") and even add more detailed information about an object (e.g., "The Mississippi River"). When dealing with large volumes of data, it's only sometimes possible for humans to manually correct all of the errors in your database. That's where data enrichment tools come in handy! Data enrichment is taking a raw data set and turning it into something more useful. It's like when you're cooking, taking all the ingredients from your fridge and turning them into a delicious meal. Rather than going through all the trouble of making something, engineers take their boring old data sets and add some stuff to improve them. That's why we love data enrichment: It makes boring things fun!