Data enrichment is the process of merging third-party data into an with an existing customer and/or prospect database or raw data. This process gives organizations more granular data on existing customers and new business, and make better informed decisions on to whom, where, and how to target opportunities.
There are two primary types of data enrichment (besides real-time and batch updating):
- Demographic is the acquisition of new demographic data (income level, marital status, home address, etc.), which is then added to customer datasets.
- Geographic is the acquisition of postal data and latitude and longitude that is then added to customer addresses in existing datasets.
Data Enrichment vs. Data Cleansing
Data cleansing usually involved two steps: first, identifying if data is still valid, and second, appending contacts with additional information. The second step of data cleansing often falls under the umbrella of data enrichment, which is a broader term that covers the process of enhancing, refining, and improving both refined and raw data sets.
Data Enrichment with the Snowflake Data Exchange
With the Snowflake Data Exchange, data consumers can browse an external data catalog to acquire new data sets that can enhance existing business data. Data providers also can publish data sets or offer data analytics services to Snowflake customers and turn their wealth of data into an asset.