When it comes to data integration and data migration projection, data mapping has proven to be an important step. Businesses and corporations can attest to the role that data mapping plays. From the onset, it influences and determines the flow and access to data. It also serves as a method of communication for the different players in the project. But what exactly is data mapping? In this article, we unpack this modern-day phenomenon to the modern-day layperson.
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What is data mapping?
Data mapping can be explained as the process of identifying and creating data connections between the different sources and targets in data. Regardless of the size of the project, data mapping often involves several common actions:
- Data transformation from the source of data to the destination
- In the case of multiple sources of data, data mapping would include compilation of data into one database and removal of any redundancy
- Specification of any data conversation rules.
- Establishment of data relationships
The role of data mapping in data integration
From the small description given above, one can begin to imagine how critical data mapping is in a data integration project. But first, let us explain what data integration is.
Data integration involves the combination of data from different sources into a single destination. The final document created as a result of data integration allows individuals, businesses and corporations to make intelligent and informed decisions.
With the current level of technology and advancement, data mapping tools are as advanced as never before. This is because of the increased volume of data needed to be sorted. Data mapping tools need to stay on toes with the needs of data analysts.
Data analysts and researchers can rely on data mapping to offer accurate and detailed relationships between the different data available. Data mapping tools enable users to see the flow of data and the history of transformations for each data set.
With different data sources, there is always the issue of data formats. With different formats, compatibility and usability of the data start to diminish significantly. Data users are also unable to comprehend and make decisions in a timely manner.
This can be streamlined with the use of a data mapping tool. The built-in features provided within the software allow for smooth transformation of data from one format to another, saving on time and reducing inaccuracies and errors.
Conclusion
Organizations and businesses are daily relying on data to make critical decisions. In addition, data is becoming more spread out and voluminous over time. A robust data mapping system could prove the difference between a viable business and a failing one.