Reltio IQ for Machine Learning


Applying AI, machine learning & deep learning to data in context


There has been a lot written about Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) as the next wave of productivity and efficiency for businesses. Some vendors even refer to the concept and technology as Cognitive Computing. While vendors have jumped on the AI, ML, DL bandwagon, the reality is that most do not fully understand the nuances and differences between each term, and how they relate to each other. 


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    At Reltio, we leverage machine learning in several ways, including:

    1. Continuously improving consistency, accuracy and manageability for better data quality (DQ), uncovering patterns, anomaly detection and assisting humans such as data stewards, to make their job more focused and efficient.
    2. Enabling a seamless foundation for the generation of relevant insights and contextual recommended actions, which can be operationalized through data-driven applications.

    What many don't realize is that the context of machine learning needs to be applied to your specific business and industry, with a focused set of benefits for each business users' role in order for it to be accurately measured, so it doesn't get labelled yet another (data) science project with limited value.

    Just as the process of aggregating data to perform historical or predictive analytics is a cumbersome and expensive process, gathering and blending all of the right data that will guarantee machine learning is effective must be the in the DNA of a Self-Learning Enterprise.   

    Bolting on AI or ML into legacy master data management (MDM) systems, or using such MDM tools to feed downstream, disparate ML tools is a path destined for failure. Reliable data, relevant insights and recommended actions via machine learning needs to be seamlessly combined into one, single cloud application, delivering both analytical intelligence and operational execution.  

    But it goes beyond just providing technology. An open ecosystem that allows you to choose and partner with technologies, and domain experts of your choice is critical to getting the most out of a still young and evolving landscape. Most companies are already trying to evolve out of their legacy MDM platforms. Getting further locked into a single vendor delivering both MDM and ML, through siloed disparate tools will not only fail to provide clarity, but may further complicate an already fragmented data management strategy.

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    Reltio IQ (Formerly Reltio Insights), a module of the Reltio Cloud Self-Learning Data Platform, brings mastered data together with big data scale interactions and transactions, into a single Apache Spark on demand environment, to quickly enable agile, closed-loop insights and action. This not only provides for faster Time to Analytics (TTA), but more relevant and accurate information through best of breed machine learning tools and technologies.

    Our singular goal is to propel the field of Human Data Science to help drive healthcare forward. Continuous data organization plays a vital role in moving us towards this vision,” said Chitra Varma, Global Commercial Leader at IQVIA. The market reception by major life sciences manufacturers to IQVIA’s Commercial Data Warehouse, powered by Reltio Cloud, has been very positive. We are excited to take advantage of the new Reltio Self-learning Data Platform release to deliver even more advanced capabilities to our customers.
    — Chitra Varma, Global Commercial Leader, Information Management Solutions, IQVIA

    RELIABLE DATA FOR ANALYTICS & Machine learning

    Reltio puts all information you need for analytics, and the use of machine learning in one place, accessible in real-time. Reliable and accurate data from master profiles, interactions, transactions, third-party, public and social media sources is consolidated for deeper analytics. When analytics run on a reliable data foundation, organizations can make better and informed decisions.


    Reltio IQ bring aggregated analytics back to master data profiles to enrich and improve data. Unlike analytics-only tools or disparate machine learning technologies, Reltio's bidirectional connectors enable recommended actions for business improvement inside user applications. The key is a "closed-loop" of Data Quality (DQ), insights, action and ultimately outcomes to power continuous machine learning.


    Faster correlation of accurate, up-to-date profile data with transaction data from multiple sources makes deployments quick and simple. Pre-configured connectors to analytic environments make leveraging reliable data easy. Data is made available to analytics apps, and machine learning algorithms in near real-time. Deployed in the cloud, you'll be up and running faster than you dreamed possible.


    With Reltio IQ you can enable traditional and non-traditional analytics, together with machine learning on a single reliable source of structured, unstructured and graph data. Automated updates of business model changes help keep up with dynamic business environments. Support for multiple representations of data based on algorithms and inference helps contextual presentation of insights. Reltio Cloud is multi-tenant, horizontally-scalable and always available. Companies can scale-up and scale-down, on demand and use compute power by type of insight and machine learning through recommended actions.