Data enrichment is the process of collecting and storing data.
The data can be any kind of information that can be represented digitally, such as a name, an email address, a phone number, or which pages are visited often in relation to when a visitor is purchasing your services.
Data enrichment can also refer to the process of gathering and storing context information about the data. This additional information “enriches” the original log with this context.
Data enrichment is critical for providing valuable business insight into your original data set. The more information that you have about your digital assets, the better you will be able to identify trends and patterns in your data and to make business decisions based on this gathered knowledge.
Data enrichment is the process of using additional information to augment or enhance collected data. The additional information may be stored in a different repository, or it may be augmented to provide more detail about the source.
Data enrichment can be used for real-time analysis where the additional data is fed back into the collector; for example, if a log parser notices that an event was recorded with no country specified, it could query a GeoIP database to obtain the country or city associated with that IP address.
An important use case for data enrichment is providing context about an interaction. This context may include things like location, operating system, browser version, and so on.
If the log entry contains only a user ID but not their name or email address, additional information can be used to enrich the log with this context so it contains enough information to be useful for analysis.
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