With the volume of data reaching unfathomable heights, the importance of leveraging and transforming data to extract actionable insights has substantially increased. However, data transformation is not an easy task to execute as data may not always speak the language. To integrate this varied data and gather some sense from it, data mapping must be used which is the process of establishing relationships between different data models.
Let us know what data mapping is and how it can be used to generate valuable insights.
Data Mapping
Data mapping is a process wherein, source data fields are mapped to their target fields. Fields can be phone numbers, names, URLs, emails, or other inputs enterprises need to create and seize for reporting as well as querying purposes.
Data mapping can vary on the basis of the hierarchy of data being mapped and the disparity between the structure of the source and target. Every business application employs metadata to elaborate the data fields and attributes that constitute data, along with a set of semantic rules that govern how data is stored within that particular application or repository.
Significance of Data Mapping
Data mapping application enables companies perform a wide range of data integration and transformation tasks. Let us see how.
Businesses need to unify and transform sources into a suitable format to carry out a host of operational and analytical processes. This can be done with the help of data mapping.
Data mapping is an integral step in a variety of data management processes including:
Data Integration
Data integration can only be successful only when the source and target data repositories have the same data model. However, having any two data repositories with the same schema is extremely rare. In such a scenario, data mapping tools can be of great assistance. Data mapping tools can be used to bridge the differences in schemas of both source and destination data fields, thus enabling enterprises consolidate information from diverse data points easily.
Data Warehousing
The process of making a connection between source and target tables or attributes is called data warehousing. With the help of data mapping, businesses can build a logical data model and outline how data will be structured and stored in the respective data warehouse.
The process starts with gathering information and comprehending the source data. Following that, a data mapping document is created; transformation rules are built and mappings are created with the help of a robust data mapping application.
Data Transformation
Data transformation is essential to break information silos present in a wide range of locations and formats for drawing insights. Data transformation’s first step is data mapping which is used to create a basic model of what changes should be made to the data prior to loading it to the target database.
Data Migration
Data migration is the process of moving data between different databases. To execute data migration, mappings between the source and target is created. This process becomes difficult and time-consuming, particularly when done manually. If the mapping is inaccurately done, not only accuracy but also the entire data migration process is severely impacted. To solve this problem, one must use a code-free data mapping solution that can automate the process to migrate data to the destination successfully.
Electronic Data Interchange (EDI)
EDI file conversion uses data mapping application to convert files into respective formats like XML, JSON, and Excel. Such applications allow business users collect data from multiple sources and utilize built-in transformations and functions to map data to EDI formats without any sort of manual intervention.
With so many features and benefits, using a data mapping tool becomes more than necessary. However, since the market is brimming with such tools, picking the right one is crucial.
Users need to first identify their requirements and end-objectives before selecting a mapping solution. They need to go through the features and specifications of the data mapping tool, then match it with their requirements to make the final decision. For example, a feature like Graphical, Drag-and-Drop, code-free user interface will suit companies who look for code- free way of data mapping.
