Data management is an important aspect of today’s data-driven businesses and data mapping constitutes an important part of it. The data management industry is growing at a CAGR of 11.2% to reach a market size of $281.9 billion by 2028, and data mapping will have an important role to play.

In simple terms, it refers to the process of creating element mappings between two distinct data models i.e., it ensures that data from a source system is accurately and appropriately translated to a target system that maintains the integrity and consistency of data.

Practically, it defines how individual fields in the source data correspond to fields in the destination data. The entire process can either be straightforward involving direct field-to-field mappings or complex where transformation rules, lookups, and aggregations are required.

For example, in simple mapping “first_name” field in source data is linked to the corresponding field “given_name” in the target database. Whereas in more complex scenarios, it might include linking “first_name” and “last_name” into a single “full_name” field.

Well, data mapping can be quite an interesting skill to learn and it offers several benefits to businesses such as ensuring:

• Data quality
• Consistency
• Integration
• Compliance, etc.

If you are interested in a career in data science, knowledge of data mapping is a must. So, check out our detailed infographic on data mapping and its importance in the world of data science now.