Data mapping

In computing and data management, data mapping is the process of creating data element mappings between two distinct data models. Data mapping is used as a first step for a wide variety of data integration tasks, including: Data transformation or data mediation between a data source and a destination Identification of data relationships as part of data lineage analysis Discovery of hidden sensitive data such as the last four digits of a social security number hidden in another user id as part of a data masking or de-identification project Consolidation of multiple databases into a single database and identifying redundant columns of data for consolidation or elimination For example, a company that would like to transmit and receive purchases and invoices with other companies might use data mapping to create data maps from a company's data to standardized ANSI ASC X12 messages for items such as purchase orders and invoices. X12 standards are generic Electronic Data Interchange (EDI) standards designed to allow a company to exchange data with any other company, regardless of industry. The standards are maintained by the Accredited Standards Committee X12 (ASC X12), with the American National Standards Institute (ANSI) accredited to set standards for EDI. The X12 standards are often called ANSI ASC X12 standards. The W3C introduced R2RML as a standard for mapping data in a relational database to data expressed in terms of the Resource Description Framework (RDF). In the future, tools based on semantic web languages such as RDF, the Web Ontology Language (OWL) and standardized metadata registry will make data mapping a more automatic process. This process will be accelerated if each application performed metadata publishing. Full automated data mapping is a very difficult problem (see semantic translation). Data mappings can be done in a variety of ways using procedural code, creating XSLT transforms or by using graphical mapping tools that automatically generate executable transformation programs.