As business continues to evolve, data becomes more integral to everyday business processes, and business users have all thrown the full force of their enterprise application infrastructures into getting obscure insights from databases. If knowledge is power, then data analytics are to growing companies what the Infinity Stones are to Thanos. In other words, data is everything.
It’s true that when you’re dealing with big data, you’re going to come across tons of data sources, data sets, and databases, and it’s the reference data you find in them that will serve as the basis for much of your decision-making. Whether you’re in the wholesale electronics industry or the financial services industry, reference data should play an integral role in developing your business strategy. Continue reading to learn how to use reference data and master data to grow your business into the powerhouse you’ve always envisioned it would be.
What is reference data?
Whenever you’re dealing with massive databases and data sets, business rules dictate that you have a set of data by which all other data sets can be measured. Without a reference point, even the most intimate and intricate data is impotent. That’s why reference data management is critical to your data processes.
An example of reference data would be a legend on a data chart that gives a broad picture of a collection of data. For instance, in a database, the reference data are the values that you see above, below, or to the side of data that indicates its importance.
To get a better understanding of reference data, let’s use the example of a database of refurbished electronics wholesalers. Let’s say there are eleven electronics wholesalers in your database, and you’re trying to get insights into all of them. Well, one piece of reference data would be that there are eleven wholesalers. If they all sell refurbished laptops and tablets, as opposed to other consumer electronics, that would also be considered reference data.
In other words, in a data set, reference data is the data that applies to all of the entities represented in the data set. It’s the data that serves as a reference point for all the types of data in a code table or database.
Why is reference data management (RDM) necessary?
When you’re dealing with different types of data from multiple sources, data quality and data integration are always major concerns. It’s important to maintain the integrity of data values for integration as well as to develop accurate and reliable data models.
Without referential data management, there’s no uniformity, authority, or data governance to ensure data quality across different databases and analytics platforms. Using RDM solutions make it easier to put different kinds of data into their proper classifications. In other words, without data integration of reference data, your master data has no importance of its own.
How do companies use reference data?
There are plenty of use cases for reference data in nearly any industry you can think of. The stock exchange likely uses reference data more than any other sector of commerce. For example, when companies on the exchange start the day, their current stock value is where it closed at the previous day. Even though the value of the stock may fluctuate throughout the day, brokers use the reference data to determine which way the stock is trending and to what magnitude.
Manufacturers frequently use reference data for supply chain management purposes. For instance, when they want to lower their production costs, they may search for companies that charge below a certain amount for their raw materials. The amount the company is willing to pay serves as their reference data, and they can find suppliers who fit into the classification dictated by their reference data.
Without reference data management and master data management systems, the managers of your data don’t have all the tools they need to make the most of it. By using reference data to set precedents for data sets, you can see the story behind the numbers.