Respected analyst firm Constellation Research's founder, chairman and Principal Analyst Ray Wang and VP and Principal Analyst, and former columnist for InformationWeek, Doug Henschen collaborated on an objective profile of Reltio. The report states "Reltio is unique in blending master data management and machine learning capabilities into a PaaS that is purpose built for data-driven applications and services."
Ovum has always believed that MDM is most effectively implemented, not as an integration tool, but as an application that ingrains domain knowledge about how specific industry sectors organize data. Reltio is applying that approach to big data, taking it a step further by applying machine learning to guide users and help them make decisions based on their discoveries about how people, products, and/or other entities interrelate.
John Wollman, Executive Vice President & Chief Innovation Officer, HighPoint Solutions discusses how Reltio provides best-of-breed master data management (MDM), coupled with the ability to perform rich analytics upon large volumes of transactional claims data through Reltio Insights.
Are you interested in bringing machine learning and predictive analytics to your enterprise? Many prospective users don't know where to start. Ramon Chen, chief product officer for Reltio, recently spoke with us about this challenge.
Maxim Lukichev, Lead Data Scientist, Reltio, talks about Reltio Insights and how it seamlessly leverages Reltio Cloud Modern Data Management Platform as a Service to power reliable advanced analytics and machine learning, to feed data-driven applications.
Some thoughts on recent trend where martech companies have shown a considerable amount of interest in acquiring smaller independent AI firms
Businesses large and small are being lured in by the potential of artificial intelligence (AI), machine learning (ML), deep learning and cognitive computing, while others are still trying to figure out how to tell them apart.
Chief Data Officer, Chief Experience Officer and now there's a new kid in the C-suite: The Chief Artificial Intelligence Officer.
Reltio Lists Our Top 5 Predictions for Analytics, Data Management and AI for 2017
Maintaining data reliability is a resource-intensive uphill task for many organizations. Companies often spend too much effort on data reviews and cleanup, but seldom seem to catch up. Most of the time, teams don’t even know what the issues are, how to look for them, and how to solve them. They just know that the data is dirty, and like a sitting on a ticking time bomb, we wait for the disaster to happen.
The sheer volume and variety of data requires the assistance of highly skilled, very scarce “data scientists”, it makes things even worse when the data is not reliable and you are essentially gambling with your insights.
Big data should be leveraged not only to respond to inquiries but also to proactively deliver information. The system should be able to make recommendations based on all the information that is available with a continuous feedback loop to improve them with each interaction.
We Skyped Judith Hurwitz, author of the best selling book Cognitive Computing and Big Data Analytics to get her thoughts about big data, predictive analytics, machine learning, master data management ... and data bathtubs!
Experts in Data Management and Machine Learning from Thomson Resuters, Amazon Web Services, and Reltio discuss the future of AI at the Nasdaq Entrepreneurial Center.
Can you prove the ROI of your data management efforts? Are you able to conquer the gap between your analytical insights and operational execution? If the answer is no to one or more of these questions, you must rethink (and reinvent) your data management philosophy.
It's easy to be seduced by the "black magic" of technology that can solve a variety of your business challenges by just asking Watson, Einstein, Siri, Alexa or even HAL, and other "humanizing" names. Beyond the hype, here are 3 critical ingredients that must be considered in order to be successful.
This year’s Big Data Innovation Summit 2017 in San Francisco tackled weighty themes to help attendees avoid costly mistakes from inaccurate data and attain best practices for harvesting data with high potential to name a few.
Hadoop, HBase, Cassandra, Graph Databases, MapReduce, Spark and the continuous stream of new technologies have changed the way data can and should be managed. However stitching together all of the pieces required to have a complete end-to-end offering and support a wide variety of business needs across an enterprise is a complex undertaking. A Modern Data Management Platform helps you keep up with this evolving technology landscape.
One of the most important issues for customers will be the trust in the data and in the results from a cognitive system. A cognitive system is only as good as the data that is ingested. Data needs to be analyzed so that the meta data is understood. This data needs to be refined so that its meaning is clear and the data itself is truth worthy. After all, the value of a cognitive system is that it creates an environment where industry experts can trust a cognitive computing system.