Data mapping is typically the first step in integration of different data models. The process is used in data warehousing to link data sets according to specific data element definitions. The standards used depend on the domain values of the model used.
In simple terms, data mapping software is used to convert data into a standardized electronic data interchange (EDI) file format and then back again so that incoming data can be matched to existing data. But this also holds true of outbound data that must be mapped to a partner's data requirements. Data mapping tools can be used at either end depending on the systems and agreements in place.
In many enterprise environments and in certain industries, data mapping can be quite complex, both in terms of the size of the data file, the number of fields involved, and the transformations that are required. Data from two different sources may be mapped to each other before they can be integrated with a third, where they are transformed again and are added as new records into a data warehouse.
Software for mapping data is used to transform information seamlessly between systems, such as a transaction loaded to web interfaces, strict formatting of healthcare codes, and more. Data mapping can transform every field in a data record to specific lengths, data types, and formats as required by the receiving system, including dropping redundant or irrelevant data fields, or combining elements into a new field. Effective data mapping tools eliminates the need for data entry or manual transformations.
Data mapping software can automate such data integration processes as:
- Transformation of data between a source and the destination.
- Identifying relationships as part of data analysis.
- Consolidation of multiple data sources into a larger, homogenous data volumes.
- Concealment or discovery of sensitive data such as the masking or de-identification of account numbers or social security numbers.
Finding the right data mapping tool
Salesforce makes it simple for data teams to map and transform every data field in a file or table to integrate smoothly with a destination table. Developers can supply conversion rules for each field so that importing or exporting data is accomplished quickly and smoothly every time, provided the structure of the fields don't change.
Most software for mapping data will utilize metadata, or data about data, to provide the information defining data objects, fields, rules, and attributes. This determines how the data is persisted in the destination system. Data integrity and dependency rules must also apply, for instance in relational databases where records are associated with a surrogate ID field, or credit card numbers may need to be encrypted.
Data mapping specifications are a form of data dictionary that shows how data is to be mapped from elements in one information system to the data elements in another. Creating a formalized specification helps to establish a clear guide for employees or project teams to follow. This helps to keep everyone on the same page to avoid ambiguities and mismatched data fields. Data mapping software can help to enforce these specifications, which could otherwise crash EDI systems or lead to unusable data.
This is a helpful feature in data migrations, where the original data is normally discarded after migration is complete, and data integration, where the original data sets may still exist separately. Data mapping software typically has the capacity to check for data integrity and abort the process or issue alerts. Otherwise, bad data may go undetected until it creates operational problems. For instance, customer service training will depend on transforming raw customer data into readable formats that help CSRs focus on customer needs.
Data mapping specifications allow data tools to determine, one field at a time, how data is transitioned from a source field to any field within a target table. This may include renaming the fields, or adding prefixes or suffixes. Every piece of information must map correctly to the corresponding field in the target listing.
The specification used by the data mapping software must include a list of attributes for all data sources, a list of attributes for the data destination, and a direct transformation between corresponding attributes.
Software for mapping data can automate any electronic integration or migration of data. However, it must also be both flexible in defining conversion rules and reliable in following specifications. Otherwise, you run the risk of losing or corrupting precious data.