By Rathnakumar Udayakumar 2 min read
July 15, 2021

We’re excited to announce that a new entity resolution service, IBM Match 360 with Watson, is now available as a base service on IBM Cloud Pak® for Data.

IBM Match 360 offers self-service capabilities designed for business analysts or data scientists to resolve duplicate person or organization entities to a point that they can use them in analytics and develop new models. The sources of these records could come from anywhere, including existing operational MDM systems or those with transactional or clickstream data. 

According to Gartner, one of the key trends in the master data segment is the move toward a more user-friendly experience. Once the domain of subject matter experts and developers, we have reimagined the configuration experience — specifically the data modeling and the matching configuration. 

Additionally, we are utilizing IBM Cloud Pak for Data services like Watson Knowledge Catalog as we start to bring together metadata management, data quality and entity resolution. Our aim is to provide existing customers with the ability to augment their master data with new sources quickly, providing a more complete view of their key entities.

We are also engaging with new customers who are pursuing Customer 360 use cases and are focused on delivering a stronger analytic base for customer data without the desire to implement a full master data management program. These new customers will also realize value by starting with virtually any source data model, linking sources, exploring entities and exporting data for further analytics and machine learning development.

But what happened to Master Data Connect? For customers with the need for a cache of their MDM AE or MDM SE entities, this use case is still supported with IBM Match 360. IBM Match 360 is the evolution of our modernized architecture, delivering on the Master Data Connect use case and many more.

Three ways customers can get IBM Match 360 with Watson

  1. IBM Cloud Pak for Data Enterprise Edition VPCs can be applied toward IBM Match 360,
  2. MDM Cartridge for IBM Cloud Pak for Data for new and existing customers looking for a full MDM solution today, with a self-service entity resolution service,
  3. MDM Modernization for IBM Cloud Pak for Data for existing customers looking to capitalize on these newly-enabled use cases.

IBM Master Data Management Cartridge for IBM Cloud Pak for Data

The IBM Master Data Management Cartridge for IBM Cloud Pak for Data is a license bundle that includes the following:

  • IBM InfoSphere Master Data Management 
  • Entitlements to IBM Match 360 with Watson on IBM Cloud Pak for Data
  • Red Hat OpenShift license entitlements.

This bundled approach to the MDM Cartridge gives customers the ultimate in flexibility with our shared entitlement model — deploying IBM Match 360 with Watson for analytical use cases described above, deploying MDM Standard or Advanced Editions for operational use cases and using them together on their path to modernization.

Get started

We encourage you to provision a beta instance here to experience the robust matching and analytic capabilities in IBM Match 360 with Watson. This IBM Cloud Pak for Data as a Service instance has full feature parity with the GA version of IBM Match 360.

Categories

Analytics  |  Announcements  |  Cloud  |  Data science  |  data-science  | 
Rathnakumar Udayakumar
Senior Product Marketing Manager

More from Analytics
October 3, 2023

IBM and ESPN use AI models built with watsonx to transform fantasy football data into insight

4 min read - If you play fantasy football, you are no stranger to data-driven decision-making. Every week during football season, an estimated 60 million Americans pore over player statistics, point projections and trade proposals, looking for those elusive insights to guide their roster decisions and lead them to victory. But numbers only tell half the story. For the past seven years, ESPN has worked closely with IBM to help tell the whole tale. And this year, ESPN Fantasy Football is using AI models…

September 19, 2023

Data science vs data analytics: Unpacking the differences

5 min read - Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to…

September 6, 2023

Financial planning & budgeting: Navigating the Budgeting Paradox

5 min read - Budgeting, an essential pillar of financial planning for organizations, often presents a unique dilemma known as the “Budgeting Paradox.” Ideally, a budget should give the most accurate and timely idea of anticipated revenues and expenses. However, the traditional budgeting process, in its pursuit of precision and consensus, can take several months. By the time the budget is finalized and approved, it might already be outdated.In today's rapid pace of change and unpredictability, the conventional budgeting process is coming under scrutiny.It's…

August 28, 2023

How Macmillan Publishers authored success using IBM Cognos Analytics

5 min read - Macmillan Publishers is a global publishing company and one of the “Big Five” English language publishers. If you're a reader, chances are good you've read a book from Macmillan. They published many perennial favorites including Kristin Hannah’s The Nightingale, Bill Martin’s Brown Bear, Brown Bear, what do you see? and some of the more recent bestsellers such as The Silent Patient by Alex Michaelides, Identity by Nora Roberts and Razorblade Tears by S. A. Cosby. It’s no wonder then that Macmillan…