Data Mapping and its importance in Data Management

Every organization deals with massive amounts of data coming from various sources. This data may be present in different formats and hence it is difficult to integrate it into a single source for the analysts to analyze and gain insights. Data mapping is an important part in integrating data and it plays a crucial role in data management processes like data integration, data migration and data transformation. Data Mapping is the process of mapping data fields from a source format to a target format. Every application has a defined schema and rules, and Data Mapping describes how the data from two different applications would be mapped with each other.

Data Mapping is an important step in Data Management:

Data Mapping is an important step in Data Integration, Data Migration and Data Transformation processes. Data Mapping logic will determine the data quality of these data management processes and any inaccuracy in the mappings will have a huge impact on all these processes.

Data Transformation:

Data Transformation is the process of converting data from one format to another format, more importantly, from source format to the destination format. It includes cleaning data by converting data types, removing duplicate data and enriching the data etc., based on the needs of the project. Data Mapping forms a crucial stage in Data Transformation. It creates a set of instructions which is needed for the data conversion to take place. Data Mapping supports data manipulation functions which are applied to data as and when it is transformed from source format to the destination format. During the data transformation process, data mapping determines how to map, filter or modify the data fields as per the requirement of the new data type.

Data Migration:

Data migration is the process of transferring the data from one application to another. Though there are many steps in the data migration process, data mapping is one of the crucial steps in the process. The process of creating maps by writing code or using scripting languages is a developer centric approach, which will impact the timelines as well as budgets. Hence having a data mapping platform like DX Mapper which provides a graphical, user friendly drag and drop and code-free interface to do data mapping, will help in migrating the data to the target source successfully.

Data Integration:

Data Integration plays a crucial role in driving data from multiple sources like applications, databases, devices etc., into a single platform. In order to have a perfect integration, the source data fields and the target data fields must have the same schema. But, it is uncommon that any two data sources will have the same schema. Data Mapping helps connect the differences in the source data schema and that of the destination and allows organizations to integrate the information from different data sources. A comprehensive Hybrid Integration Platform like DXchange Integration Cloud provides business agility to enterprises by connecting applications, data, devices both on-premises and in the cloud and helps the enterprises to be digitally transformed.

Conclusion:

Data Mapping is a key step in many stages of data management processes like data transformation, data integration and data migration. Data mapping is a complex, resource-intensive process if done manually and requires complete knowledge about source and target data fields. Hence it is important to choose a sophisticated data mapping tool like DX Mapper having a powerful, user friendly drag and drop, intuitive no-code interface to prevent errors and reduce the time taken for mapping data. As organizations continue to look to integrate data from various sources, the priority must be to choose the right data mapping tool that will be the best fit for an enterprise.

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