Data has become one of the essential commodities in today’s fourth industrial revolution world. The use of software and IoT-connected devices by both individuals and businesses is consistently increasing. As the world’s reliance on big data increases, data professionals require efficient data solutions at all times. And as a result, new innovations like master data management keep emerging. This article delves into the topic of reference data, which is a fundamental input of data management.

Reference Data Defined

The big data world as we live today requires businesses to collect several data types, including reference data. Reference data is a unique subset of a business’ metadata. It’s mainly used to define identifier characteristics in a business’ master data management efforts and covers a wide range of data values and has many business use cases. Companies also use it to enhance communication and flow between their enterprise and departmental applications.

There exist two main varieties of reference data: multi-domain or real-time data. Multi-domain spans across multiple functional areas of a business. With master data management solutions, businesses can combine data from all these areas, including HR, finance, etc., into a centralized platform making data access easier. Real-time reference data makes metadata tagging more efficient. It has become a favorable option for IoT application authors who seek big data lakes to store their ever-increasing streaming data.

Also, real-time reference data has become a mainstay in the financial brokerage and securities industry due to its accuracy with large numbers. Secure identifiers used in the finance industry to complete transactions are all a form of reference data.

Some general examples of reference data include:

• Financial hierarchies
• Currencies
• Country codes
• Business processes
• Customer segments

How it Works

Reference data systems collect data from various sources across an organization’s data infrastructure. The data management approach begins by integrating all these data into a central reference data unit. After standardizing the reference data, businesses can now discover, profile and make meaning out of their reference data.

Further steps are then taken to govern the reference data before making it accessible across an enterprise. Quality checks are conducted before reference data becomes available to applications in a data enterprise. This due diligence is a great way to avoid data replications during the integration process.

Main Benefits

Reference data is a key input in the reference data management process. Some of its benefits include the following:

1. Reduced IT Overheads

Reference data management typically requires a central unit for storing and managing a company’s reference data. This translates into a reduction in costs needed to procure and maintain multiple storage units for a business’ data set. Also, reference data management affords data professionals a cost-effective approach to managing data sets.

Businesses can manage complex relationships across products, vendors, locations, and customers with more control. Increased control over operations means fewer mistakes in business output and ultimately less money to repeat the process.

2. Agile Operations

Many companies opt for the use of reference data due to its associated flexibility. Real-time reference data, for instance, can make it easier to model and test business decisions in virtualized environments before the findings are applied. This agility in operations is helpful for businesses, especially in the time of COVID-19, where new business realities require unique solutions.

3. Risk Reduction

Reference data offers businesses more guarantee for data security, accuracy, and compliance. Managing a secure, accurate, and compliant data set reduces the tendency of incorrect business decisions.

4. Improved BI Reporting

Modern businesses use business intelligence solutions to transform complex data into comprehensive insights. Reference data and good data analytics can render a company’s business intelligence more accurate and reliable.

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