The journey from traditional MDM to Golden Records: A Must for Modern Businesses

By Suki Dhuphar, Head of EMEA at Tamr.

  • 3 weeks ago Posted in

Organisations have long faced the monumental challenge of maintaining reliable data, with siloed systems having a detrimental impact on business decision-makers and customers alike. That’s why Master Data Management (MDM), with its promise to unite and manage data efficiently, initially attracted so many business leaders. The potential to bring together every type of data within an organisation (consumer, product and supplier) into one true ‘golden record’ by applying rules-based methods led many to believe MDM would be the solution needed to bring uniformity to an enterprise’s data.

But despite the hype around MDM, it could never reach the heights that business and data leaders hoped for. Data teams quickly learnt they could not achieve Golden Records because the process of constantly writing, modifying and maintaining rules as their organisational data changed was far too resource and time-intensive.


AI-powered data mastering


The answer to mastering organisational data requires business leaders to look beyond traditional MDM to AI-powered data mastering. Such solutions empower businesses to improve their data quality by processing large volumes of customer data, giving them a greater understanding of customer behaviour to fuel more personalised experiences and customised offerings. This can give organisations an edge over competitors and improve experiences for customers.


Saving time and money


Comparing AI-powered approaches with traditional MDM provides more reasons to switch to this cutting-edge data management technology. MDM has manual processes, so it can take months or years before any benefits are seen. Whereas, the automation and efficiency of AI-powered mastering capabilities mean businesses can formulate and deliver Golden Records in a matter of days, improving the time to value and reducing the cost to the business.


More accurate decision-making


To feel confident in its decisions, every business needs to ensure it is basing decision-making on accurate and up-to-date data. The manual processes required for MDM, however, often lead to questions over potential errors and inaccuracies in an organisation’s data. On the other hand, automated processes are far more reliable, while reducing the time it takes to curate and match data by up to 90%. AI-powered data mastering ensures that entities are resolved efficiently and allows data teams to use their valuable time elsewhere within the organisation.


Superior business insights


With traditional MDM, the process of unifying data is a manual and laborious task, which data teams must continuously work on to maintain data quality. Instead, AI can streamline the process of aligning all of an organisation’s data sources and enriching them with third-party sources. This improves business insights as they are based on more complete data with richer context.


Improved data integrity


Traditional rules-based MDM does not adapt as quickly to new data sources as AI-powered solutions. By leveraging real-time API integrations to dynamically connect source systems, AI-powered solutions keep Golden Records up to date as the data landscape evolves. This is essential for long-term data integrity as organisations grapple with the challenge of managing vast amounts of diverse data sources. And the result is precise and reliable analytical insights that reinforce business priorities at the operational and customer level.


Human and AI collaboration


While AI-powered solutions are far less time-intensive for data teams than traditional MDM solutions, they still require human domain knowledge when processing complex, noisy and unclear data. Human collaboration with AI is essential for refining and enhancing data, identifying and resolving errors in its output, or making judgement calls for cases that are too complex for the AI or where it does not have the relevant context.

This is important because while Golden Records must be thorough and continuously updated, they must also be contextualised within the real world. So, AI lays the groundwork for efficient and scalable data management by handling the majority of data processing. Data analysts can then apply their domain expertise and analytical insights to create a clean, accurate and reliable version of the data. This streamlines the entire data management process and delivers outcomes neither could achieve on its own.


A necessary evolution in data management


We are seeing a huge transformation in the way businesses manage their data as a growing number of organisations transition from traditional MDM to AI-powered Golden Records. This is an evolution which transcends technological advancement, allowing businesses to stop viewing their complex data as an obstacle to overcome and instead realise the added value it can bring to their operations, with lower costs and more precise, resilient data.

The increasingly complicated data landscape requires AI-driven solutions which embrace human involvement and put the power of data back into the hands of businesses. For organisations wishing to utilise their data for improved decision-making, market competitiveness and customer experiences, it is clear that the future of data management lies in AI-powered golden records.

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