What is data mapping, and why is it important?

As simple as it may appear, the process is fraught with complexities and pitfalls that, if overlooked, can jeopardize the success of your software development, migration, or integration initiative.

Data mapping is rarely done on its own. It’s typically a part of the data journey within a larger project. Every time you need to change an existing data structure or establish a new one, you are highly likely to do data mapping as part of this process.

Data mapping is essential during the following initiatives:

And how exactly can data mapping help with the initiatives described above?

Each application in your IT infrastructure generates data, and these various data sources typically use unique structures or schemas.

Consider a scenario where a single data element from one structure corresponds to a combination of elements in another structure. For instance, a single ‘full_name’ field in one database might be equivalent to the combination of ‘given_name’ and ‘family_name’ fields in a different database.

Furthermore, there are situations where you may need to perform a mathematical calculation to align data fields. For example, to match the ‘expiration_date’ field in the destination structure, you might not find an exact counterpart in the source. Instead, you might calculate the ‘expiration_date’ by adding the ‘validity_period’ to the ‘production_date’.

By hiring data specialists, such as those from ITRex, you’re essentially bringing in experts who can align all the technology systems with different schemas. The result? Your operations run more smoothly, decisions are based on accurate and consistent information, and you avoid the costly misunderstandings that can occur when systems misinterpret each other’s data.

In the table below, we have highlighted several methods for data mapping, as well as the benefits, drawbacks, and suitability of each approach.

A digital health startup approached ITRex to extend the functionality of their mental health portal. The company wanted to integrate data from different EHR and EMR systems into their web portal database to give doctors access to patient information, such as demographics and medical history.

Essentially, this was a data integration project that required data mapping from the source systems (EHR and EMR systems) to the target system (the startup’s database).

As the first step, our data expert opted for Redox as a tool that can automatically integrate data from EHRs and EMRs of various clinics and deliver it as a JSON file containing one unified dataset through its API. Next, the data specialist manually mapped the data fields from the Redox API to the corresponding data fields in the client’s database. This was a challenge as much of the Redox data did not have a direct match in the portal’s database. For instance, some data fields that Redox delivered as a single entry corresponded to an aggregation of entries in the portal database. So, our expert had to parse the single entry and break it into multiple tokens.

Furthermore, some of the Redox data was not understandable and not relevant to this project. Our expert communicated back and forth with Redox engineers to clarify different aspects and coded the mapping rules into a script so that all information on new patients can be automatically positioned in the correct fields in the future.

Thanks to the exceptional technical knowledge of our data specialists and their meticulous attention to detail, the portal seamlessly integrates with various EHR and EMR systems used by mental health facilities across the USA. The solution provides a wealth of information on patients’ well-being, empowering physicians to make better-informed decisions.

The short answer is yes.

You can perform the data mapping process without any external consultation.

However, it requires a solid understanding of the business processes, the nature of the data collected, and how data mapping tools work (if you are planning on using any). So, you are likely to invest in specialized training and let your employees drop all the other tasks they have at the moment and focus exclusively on the mappings. And even then, the process is likely to take a long time.

Your internal team may understand the fundamentals of your data, its structure, and how it’s used in day-to-day operations, but they may not have a complete overview of the data flow or the specialized skills required for data mapping.

Data specialists, however, are a different story. They’re not just familiar with data mapping; they’re pros at it, with a wide range of experience across various systems. Their expertise means they can do the job quicker and also recommend improvements to your databases.

These changes can make everything run smoother and faster. For instance, your team might be familiar with how to map the data, but if the database responds slowly, it will slow down the related processes. Data experts consider the overall scope: they analyze your data and plan how it will integrate seamlessly into the organizational workflow. They can often anticipate possible issues and prevent them. This involves selecting the appropriate storage, ensuring that your data loads efficiently, designing indexes, and guaranteeing the optimal performance of your database in the future.

So, your data mapping initiatives will be more successful as a collaborative effort between subject-matter experts within your organization and external data specialists.

One of our clients had an online collaborative platform to capture usage insights in software products, and they wanted to build a reporting tool to go along with it. The company felt confident enough to do the mapping internally. But when they submitted the results, some key aspects were missing.

First, there were some crucial data pieces that the client simply couldn’t find. They knew they stored it somewhere but couldn’t identify the storage unit. Our data experts used reverse engineering to understand the business logic and then applied formulas to calculate and aggregate the missing data.

Second, some data required for the reporting tool was simply not collected by the platform. We advised the client to make particular changes to their product to start gathering and cleaning up the missing information.

If you decided to do the mappings in house, here are five data mapping steps that will guide your team through the process:

Whether you decide to work on data mapping alone or hire an expert, here are some best practices that will help you get through the process.

We are an experienced data management company that has helped many clients on their data journey. We will be happy to assist you with data processing, whether it’s a part of your digital transformation, data management initiatives, or integrating/building a new software product.

Also, drop us a line if you are not satisfied with your current reporting and analysis processes. We will help you transform your data to extract additional insights to support your business decision making.