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Data Quality, The Foundation to Achieving 360° data views you can trust

By Kelly Sun posted Thu March 30, 2023 12:33 PM


Many companies strive to have a 360-degree view of their data to personalize their customers’ experience, present the next best offer, track trends, and identify inefficiencies. Having a trusted, comprehensive 360° view is the golden ticket to improved business productivity and decision making. In contrast, organizations without the view can run into all sorts of business risks, including high costs (just fixing data alone!), poor marketing strategies, missed sales opportunities, and unreliable compliance reporting.

Unfortunately, in a recent Gartner report, only 14% of organizations have achieved a true 360° view of their customers and enterprise data. One hallmark that distinguishes successful implementations of 360° view from failures is the maintenance of high-quality data1. With data being generated constantly and stored in warehouses, data lakes, and CRMs, true high-quality data can only be obtained through consolidating core data from these disparate sources.

But how does all the data come together in a trusted fashion?
IBM tackles this challenge with ML-driven governance capabilities to connect associated data across ecosystems.
IBM Match 360 with Watson provides an out-of-the-box matching algorithm that enables organizations to connect external data to internal sources without compromising on governance and privacy. Match 360’s probabilistic matching algorithm leverages techniques such as likelihood ratio theory to assign a percentage indicating the probability of a match, and it can determine links between records with complex error patterns. By leveraging Match 360’s advanced algorithm, businesses can enjoy a short time to value, generating and reaping the benefits of quality data faster than ever before.

The tuning power of pair analysis
Furthermore, depending on the organizations’ core data requirements, users can fine tune the algorithm to match records on selected attributes and thresholds. To kick off the process, the users simply need to request a pair analysis, using real data based on the records provided, and the pairs selected by the system will be the ones that inform the algorithm the most. This phase allows decisions to be made by individual users and provides the option to adjust the matching engine configuration to meet their business criteria.  After completing pair reviews, the tuning process for weights of each attribute will be triggered.

The tuning occurs automatically without requiring any additional human intervention. This adjustment will then apply seamlessly the next time new data is ingested, allowing the algorithm to automatically match records according to the desired specifications. The ability for Match 360 users to fine tune the algorithm means that your 360° views can quickly adjust to the changing nature of business.

Pairs analysis

Learn more about how Match 360 does Pair Analysis in the Data Threads: Pair Analysis in Match 360 blog

Setting the right autolink threshold to save time for data stewards
Finally, the algorithm leverages a threshold which allows users to determine the cut-off percentage of what pairs are to be considered a match and non-match, called the autolink threshold. This percentage is of a comparison score of two records. This enables users to configure how their matching engine labels each pair of records - anything above the threshold will be automatically considered a match, while anything below will be considered a non-match. An optimal autolink threshold can save data stewards valuable time by reducing the amount of data that requires manual review, while maintaining a high level of trust and accuracy.

Going Forward
Match 360’s probabilistic matching algorithm, coupled with pairs analysis and
the autolink threshold, serve to provide a best-in-class matching experience which results in high quality matches and a trusted single view of an enterprise. With the help of Match 360, organizations will be able to save time from manually correcting incomplete, inconsistent, and inaccurate data, ultimately improving the organization’s productivity and business outcomes.

Here at IBM, we are dedicated to helping organizations achieve better business outcomes through improving data quality. To learn more about data governance, and how businesses can unlock data trust and value with intelligent matching and de-duplication, sign up for our upcoming webinar!

1Blum, K., LoDolce, M., & Omale, G. (2022). Gartner Marketing Survey finds only 14% of organizations have achieved a 360-degree view of their customer. Retrieved from