Data mapping is a very important process in data integration. In fact, it is the first step in several tasks associated with data integration, which include data transformation or data mediation between a data source and its destination; identification of relationships in data which is vital in analysis of data lineage; discovery of sensitive data including the last digits in a social security number; or consolidation of many databases into one while identifying redundancy.
Several organizations today are striving toward the common goal of uniting business and data applications in order to increase productivity and efficiency. These goals have been translated into trends in data management including Enterprise Information Integration (EII) and Enterprise Application Integration (EAI).
These technologies try to answer questions on how organizations can integrate data meaningfully from several disparate systems, so companies can better execute and understand the very nature of their business.
Many companies need to map data and translate these data between the many kinds of data types and presentation formats that are in wide use and availability today, in order to interconnect business more efficiently.
There are several ways to map data using procedural codes, using XSLT transformation or using tools with graphical interfaces. Newer methods of data mapping include evaluating actual data values in two data sources and automatically discovering complex mappings between the sets at the same time.
The data being stored in data warehouses today is of higher volume than what is stored on databases and XML based applications. Both of these applications usually can’t provide an efficient way for presentation of data to company data consumers, customers and partners.
In addressing these problems, several XML based single source strategies have been developed. However, there is still a lack of multiple transformation stylesheets for each desired final output, within these supposed solutions.
There are several software applications to address these problems. This software helps publish XML and database contents by allowing the end user the ability to create graphical designs which can simultaneously produce stylesheets with data mapping for XML or data from relational databases and come up with documents in HTML, Word, RTF or PDF formats that are effectively laid out.
Data-driven mapping is the newest approach in data mapping and involves simultaneously evaluating actual data values in two data sources using heuristics and statistics to automatically discover complex mappings between two data sets. This approach is used to find transformations between two data sets and will discover substrings, concatenations, arithmetic, case statements as well as other kinds of transformation logic.
The extensive use of data mapping combined with a company’s vigorous data warehouse architecture and business intelligence system can definitely become an orderly, efficient and effective day to day business operation.