We live in a world ruled by data. Today, all the organizations are dealing with ever-increasing enterprise data as the data sources are expanding rapidly. To enable the smooth migration of data between different sources and to get the maximum business value out of it, organizations must do data transformation efficiently to get the insights for further decision-making. However, this data has different formats, language, and schemas, hence there needs to be a way to integrate all the data sources. This is where a Data Mapper comes into play. A Data Mapper is a tool that helps in the mapping of data fields from a source format to a target format. It not only helps in mapping but also ascertains meaningful relationships between separate data files/formats.
Data Mapping is the first step for a range of data integration tasks. As the organizations worldwide are dealing with multiple business applications hosted on the cloud, on-premises or hybrid environments, it becomes imperative for them to have a robust data mapping system in place to make sure the various applications are able to communicate with each other, and thus providing data in a unified format for businesses to take actionable steps. With a data mapping tool, one can map data hosted at any of the environments with each other. For successful data integration projects, it is crucial to deploy the right data mapping tool that easily maps the source and target fields with a simple drag and drop function. A powerful graphical data mapper tool such as DX Mapper can help in your data transformation pursuits with a range of supporting features such as complex data manipulation, interactive debugger, structured and unstructured data mapping, and EDI data mapping. Through this blog, we will talk about the few important features that one needs to pay attention to while evaluating a data mapping tool –.
• Data Mapper Feature 1 – Presence of No-Code Functionality – A no-code interface functionality provided by a data mapper will allow the business user, even with no technical expertise to create maps easily. This will make sure all the business applications are mapped seamlessly and complex integration tasks are carried out with minimum technical intervention as no coding is required. Along with that, interactive features such as the graphical interface for visualizing, manipulating mapping projects and ease-of-use of a data mapping tool are important as it enables the end-user to carry out the data mapping with a simple drag and drop function.
DX Mapper a powerful data mapping tool which completely works in a no-code environment for mapping tasks of any level of complexity. Mapping is done on an interactive dashboard through a simple drag and drop option which is fast, secure and efficient & with a great ease towards list mapping and handling level mismatches.
• Data Mapper Feature 2 – Presence of Data Manipulation Functions – Many a time, multiple applications data fields need to be merged or operated before carrying out the actual data mapping. A pre-defined set of transformation rules need to exist in the mapping interface to govern the way data moves between the source to target schema. An ideal mapping tool would have an extensive library of inbuilt functions that can be applied real-time to various fields to produce the desired input for mapping.
DX Mapper provides an extensive list of data manipulation functions such as string manipulation functions, mathematical functions, datetime formatting, decode/encode, list functions and user-defined functions, with an ability to import functions/methods from custom libraries/jars. Creation of multi-step reusable composite functions such as ‘If-Else’ required to support complex integration tasks is also supported by DX Mapper.
• Data Mapper Feature 3 – Supports Structured/Unstructured Formats – A good data mapper tool should support multiple structured formats (Relational Databases, XML, JSON, EDI, IDOC, Flat files (fixed length and delimited), CSV, etc.) and unstructured formats (PDF, IoT streams, Emails, Social media, Website, etc.). Once the source and target data structure are selected, a data mapper will map the corresponding fields creating the output in the desired schema.
DX Mapper supports all kinds of structured and unstructured formats for data mapping. A user can map between the same formats or between different formats easily. The interface of DX mapper represents the structural data in a hierarchical tree structure, making it easier for the user to map from source to target formats.
• Data Mapper Feature 4 – Supports EDI Mapping – For a long time, organizations around the world are communicating through electronic data called EDI (Electronic Data Interchange) as the data exchanged through it is secure and follows the standard EDI (recognized by industries) to make data processing faster. A data mapping solution should read the data from different fields of an EDI document and map it with the desired output schema file.
DX Mapper supports standard EDI (X12, EDIFACT, HIPAA, etc.). A user can map between this EDI by selecting appropriate EDI specification within the DX Mapper. Here users can customize EDI standard schemas per their requirements, along with applying custom code list values. This type of mapping is generally useful in the case of B2B integrations. DXMapper supports EDI parsing out of the box and comes at no additional cost.
• Data Mapper Feature 5 – Supports Preview Functionality – Data mapping requires the mapping of multiple fields together. Sometimes the number of fields are in hundreds and thousands. In such a scenario, a preview functionality helps a business user immensely to intermittently check the progress of mapping done so far before testing it out at the completion. A good data mapper tool should have this functionality to enable the preview of data mapping done on the interface designer.
DX Mapper allows preview functionality to check the current process mapping progress before the test mode. Hence, a user can make changes in case some fields are mapped incorrectly before completing the overall mapping. This not only saves time but also improve efficiency and gives control to the user to stay at the top of the mapping done by them.
• Data Mapper Feature 6 – Reusable mapping – > Many a time, same condition or manipulation function needs to be applied to various data fields. Instead of using the function, again and again, fields having common functions can be clubbed together for mapping. A good data mapper should offer this feature as it is particularly helpful when one is dealing with hundreds and thousands of data fields.
DX Mapper allows a special feature called blocking which can club the data fields with the same conditionality/ functions together. Hence, a user ends up saving time and effort in applying functions separately to the data fields
Conclusion – As the world is inching closer to embrace connected devices and digital technologies in day-to-day life, one cannot afford to overlook the role of data mapping in connecting and integrating all these applications. Also, with more and more organizations opting to use multiple applications, data mapping becomes the first step in their integration pursuits. It not only facilities the automation but also supports an organization in their digital transformation journey.