April 29

Why is Data Mapping Essential for Data Integration?


The 21st century is full of amazing technological transformations. Apart from everything, one of the most powerful things of this era is Data. You can consider Data as the fuel for the success of almost everything these days. However, this data is related to specific things only. Meanwhile, the technologies are evolving and most of the things are under the process of integration.

This is mainly done for a better experience and data plays a huge role in successful integration. As mentioned above, data is specific to specific fields and the difference in fields makes it difficult to integrate this data. So, to make everything perform very well and seamlessly, the data integration process becomes necessary.

However, it is still not possible to do without data mapping. So, here we will be discussing why data mapping is essential for data integration.


What is Data Integration?

If we take a look at the different types and fields of data, there will be a lot. Some of the most common ones are B2C data and IoT data. Taking a look at the specific domains of these two types of data we will see that these are different. It is because the B2C data is about the business and their relations with their customers.

However, the IoT data will tell a separate story. As we know that combining these two will bring a lot of benefits. This process of combining the data of 2 different domains is known as data integration.

What is Data Mapping?

There are a lot of differences in the fields and rules for data collection while the data is being collected for a specific domain. It is because that data is needed to perform specifically for that field. However, when integration is needed, the difference in fields causes a lot of issues.

Data Mapping is the process that is used to combine the data of different sources and destinations to provide some meaningful information. It requires complete knowledge about the semantics of different sources and destinations of data.

This is the process that also provides the rules for how the data will be mapped and integrated from two different elements. So, we can say that data mapping is crucial and necessary for the integration of data between different elements in a seamless manner.

Why is Data Mapping Essential for Data Integration?

Now that you know about what is data mapping and what data integration is. Let us discuss why data mapping is essential for data integration. One may think that the difference of fields may be the only reason why mapping is essential for integration.

Although it is true, it is not the only case. It is because there are some other reasons as well. So, here we will be elaborating on those reasons.

In Data Transformation:

Whenever data transformation or integration is needed, mapping is necessary. It is also the very first step in the process because it makes the sources’ and destinations’ data able for integration. When we are talking about data mapping, there are the way data maps from the source to the destination.

The data mapping process or the tool takes care of this work and it governs how the data is in the process of mapping. Not only this but the mapping process also helps when the data is under usage between multiple data manipulation functions. These are the functions that work in the applications for using different types of data.

So, here the data mappers of the mapping process help in handling the structured and unstructured data types, files, and formats. In this way, each part of the data is mapping to the respective fields where it is necessary.

So, finally, the data only gets in the desired schema. In all of this, the data mapping part helps to keep the process from all the complexities that would happen in the final data.

In the Integration process:

As we were discussing earlier that data has become the fuel to success in this era of technologies. Different companies need data regularly. Here things get complex if the data types or specific sentiments are not the same. It is because of all the complexities created in the final data.

So, mapping helps here by combining the data into a useful form in a faster manner. A simple-to-use interface that solves every challenge that comes in the way of data integration helps here. This process and the tools for the process also support scalability and flexibility for even efficient results.

Apart from saving time it also gets rid of all the errors. Over the long run, its benefits in terms of speed are very effective for the company’s matters.

Data Integrity:

Data is not all about the useful information it holds. It is also about the quality and it is very important to maintain. While the data integrates it loses its quality if certain parameters are not under full control, checks, and balance. However, the mapping process takes full responsibility for the data integrity.

It is because it ensures that three are no errors or mismatches whatsoever.

The mapping tool also makes sure that there are no differences and gaps in the data from sources and destinations.

At the same time, this tool ensures that the data is mapping on the right schema according to the requirements and the source.

In all of these ways, mapping keeps the data safe from any errors so the output will be correct. This way of maintaining the data means that the data mapping is keeping the integrity of data safe across sources and destinations.

Final Words

Using data from different domains is very important when the technologies combine. It is because there is no other way to get that much useful information. Data integration is what makes it possible.

However, it is not easy to integrate the data manually because of the huge size of data models and the huge chances of making errors. So, data mapping is essential for this integration process. It is because of all of its benefits that we were discussing here.


Data Integration, technological

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