Data mapping involves extracting, transforming, and loading data from multiple sources into a centralized database. In other words, it’s joining different data sets with varying definitions to make them accurate and usable at the ultimate destination. Done correctly, data mapping can remove human error from your business processes and help identify data privacy issues, saving you time and boosting productivity.
The primary data mapping techniques are as follows:
1. Manual Data Mapping
Manual data mapping gives you complete control over your data because by manually linking your data sources with code, you can customize a data mapping solution for your company. However, once datasets start to grow, this method becomes inefficient regarding time and resources.
Best recommended for: small databases or processes that will only occur once
2. Semi-automated Data Mapping
Also known as schema mapping, this technique hybrids both manual and automated processes. A developer creates schemas by using software to connect similar data sources (e.g., drawing lines, drag-and-drop functions, smart clustering, etc.) and then runs a code to finish the data conversion. Another team member checks the data and makes any necessary changes.
Best recommended for: small databases, small companies, or companies on a budget
3. Fully Automated Data Mapping
Automated data mapping is ideal for anyone who doesn’t have access to a coder, because the tool allows you to complete the data mapping process without coding. Software will allow you to compile and analyze data regularly while also easily scaling with your company. However, your staff may have to be trained and the software may carry a cost.
Best recommended for: large companies or companies aiming to scale quickly
Conclusion
Today’s fast-paced and data-rich environment requires businesses to have access to accurate and usable data. Adding structure to your data through mapping makes it easier to understand and will also help you identify any risk areas where you may not be complying with policies. Make sure to fully understand each data mapping solution to choose the one best suited to your company.
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