[A Comprehensive Guide] What Is Data Mapping? Explained Here [MiniTool Wiki]

What Is Data Mapping?

Data mapping is an important process in Data Analysis. To give an accurate and quick result, it is important to link data between two distinct data models and migrate and map the data in the right way. Two data models are given, between which the corresponding relationship of data elements is established.

Data mapping is the first step in many data integration tasks such as data migration, data cleaning, data integration, semantic web construction, P2P information systems.

So how does the data mapping process work? We can conclude this whole process into five parts and if you hope that work on your task, it is advised to use a professional data mapping tool that can save your time and improve the feasibility.

Related article: Data vs Information: Difference Between Data and Information

First of all, it will locate the data in question, creating necessary formats and determining the structure, and then find the correlations to map the source data’s tables and fields to the destination data’s. After that, the data mapping will start after testing and a maintenance plan will show up.

Besides, data mapping is closely related to ETL (Extract, Transform, Load). Typically, data migration consists of three stages: extract, transform, and load, also known as ETL. But during this process, it requires a clear rule to determine how to extract it, how to convert it, and where to load it.

Therefore, data mapping is needed to define these rules, which is parallel to the software design and development, data mapping is equivalent to software design and the implementation of ETL code to software development.

There are some activities you may need to carry out in data mapping:

Data Warehousing – this kind of process can collect and manage data from varied sources to provide meaningful business insights.

Data Migration – it used to select, prepare, extract, and transform data and permanently transfer it between data storage systems, data formats or computer systems.

Data Integration – during the data integration, the data residing in disparate sources will be consolidated into a single dataset and the users will receive a unifies view of them with consistent access and delivery of data.

Data Transformation – it means a process of converting data from one format into another one.

What Are the Data Mapping Methods?

To map data, there are some data mapping techniques a company will use.

Manual Data Mapping

It refers to that developers connect data sources and document the process using code languages such as SQL, C++, or Java. For some complex mapping procedures, the manual data mapping may fail but it works to handle one-time data injections or custom data types.

Semi-Automated Data Mapping

This method means that developers can switch between the manual and automated data mapping methods. The difference from the automated data mapping lies in that semi-automated method includes an operator starting the process and machine finishes while automated method starts and finishes it with minimal operator assistance.

If you have a limited budget with a demand to handle a small quantity of data for various migrations, integrations, and transformations, it is recommended to use semi-automated data mapping.

Automated Data Mapping

Fully automated mapping can be used to smoothly upload new data and match it to their existing schemas. This method can cope with all kinds of data mapping even though you are not a developer.

This method can eliminate human-made errors, rapidly discover mistakes, and easily optimize the process. Besides, it can detect and reconcile different data structures to deliver an accurate view of your systems.

Apart from the above three commonly used data mapping methods, there are some other available method you can learn, such as schema mapping method, on premise data mapping, open-source data mapping, and data mapping on the cloud.

If you need data mapping tools, here are some recommendations you can choose, such as Talend Open Studio, Pentaho, AtomSphere, Astera, and HVR Software.

Bottom Line:

What is data mapping? To better understand the data mapping definition, this article has given you a series of examples and some other information about that. Hope this article can resolve your concerns and if you have any other question, please leave your comments.

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