Information is the most valuable resource in the world, and it’s all around us. That’s why companies invest billions of dollars every year into managing and exploiting the massive amounts of data they generate and collect. Of course, when you handle as much data as companies today do, it’s important to ensure the accuracy of information through data management.
Reference data is one of the most important types of data, and how you manage it can make or break your company’s business processes. This article is all about reference data management (RDM), who uses it, and why. Enjoy!
What is reference data?
Before we get into the ins and outs of reference data management, it would help to have a working understanding of master data and reference data. What does master data have to do with this? Well, reference data is a subset of master data, and RDM is a task within master data management (MDM). So, RDM and MDM are inseparable.
Master data is data that provides context about other business data, such as customer, product, and business location. Reference data is master data that is used for categorizing data. For instance, the name of a country would be master data whereas country codes are a type of reference data. Names of cities and neighborhoods are master data, and postal codes are reference data. Now that you understand reference data, we can get into the RDM meaning.
What is reference data management?
Reference data tends to change slowly over time. That means that it’s easy to miss changes in reference data, which can lead to problems with data quality.
Reference data management is all about ensuring the integrity of reference data across multiple platforms. Reference data management solutions enable business users to run various processes on reference data, including analytics, migration, and more. Using a hierarchy data model enables companies to prioritize different types of data. Furthermore, RDM solutions make data governance easier for master data and reference data.
Who uses RDM?
One of the best ways to get an idea of the importance of RDM is to see how it’s used in the real world. The good news is that there are plenty of use cases for RDM solutions in various sectors of business and service.
The financial industry is one of the most reliant on customer data. Financial institutions, from banks to insurance companies, use company and customer data to make their most critical decisions. Data governance enables these companies to automate many financial services, including building investment portfolios and tracking stocks.
As you can imagine, the healthcare industry also relies heavily on RDM solutions. There’s no industry where data quality is more important than in the healthcare industry. Medical professionals use client data to prescribe medications and new treatments. They use RDM solutions for various practices, from testing medications to keeping medical records.
Why is it important?
So, why is reference data management so important? The short answer is that data quality is critical to our society. Examples of reference data abound, from postal codes to medical code lists, and reference data values need to be consistent across various databases.
Data is one of your company’s most important assets, and it would serve you well to treat it as such. Reference data enables you to categorize master data and get more in-depth insights from it. That’s why it’s important to use the right tools and best practices to ensure data quality.
Reference data governance is a relatively new discipline in data science, and companies are already seeing many great benefits from implementing it. It makes master data management simpler for managers of data and enables companies to trust their data insights. Indeed, the right RDM system can be a great boost to your business.