Written by Jeff Wai and Katie Kupec, IBM Match 360 Product Managers
Cloud Pak for Data 4.7 is out now, with tons of great new features and capabilities - and Match 360 is no exception! We’re excited to bring you one of our most feature-packed releases since our initial launch, ranging from new data quality capabilities, extended data privacy, to new streaming capabilities and the ability to specifically define entity attributes for digital twin use cases.
New data quality workflow helps data stewards remediate potential match issues
Use the new IBM Match 360 potential matches workflow to fix potential matching issues in your master data. Streamline your data stewards' workflow by defining the range of matching scores that qualify for clerical review, then create governance tasks to help data stewards make decisions that enhance confidence in your master data.
To see the new data quality workflow in action, check out the later part of our Unlock data trust and value with intelligent matching and deduplication webinar for a full demo.
The potential matches workflow provides the framework that data stewards can use to:
Quickly generate governance tasks for potential matching issues in your data or a subset of your data.
Review and remediate the generated tasks by making match or no-match decisions on records for which the matching algorithm cannot make a confident matching decision.
For information on configuring the potential matches workflow, see Configuring master data workflows.
For information on identifying, reviewing, and remediating potential match issues, see Remediating potential matches to improve data quality.
Monitor confidence in your entities with a new data quality dimension
IBM Match 360 now contributes a new entity confidence data quality dimension to the Data quality tab for an asset in a project. Entity confidence measures the percentage of master data entities in the system that IBM Match 360 is confident are complete and accurate. You can improve an asset's entity confidence score by tuning your matching algorithm or remediating potential match issues.
For more information about entity confidence, see Remediating potential matches to improve data quality.
IBM Match 360 protects sensitive data, as required by your governance rules
When you associate IBM Match 360 with a governed data catalog that uses data protection rules, IBM Match 360 enforces the rules by masking sensitive data.
When you are working with governed data assets in the master data explorer, a shield icon on an attribute name indicates that its values are masked by a data protection rule. Governed data is also protected when it is accessed through the IBM Match 360 API.
For more information about using data protection rules with IBM Match 360, see Working with governed data in IBM Match 360.
Define, store, capture and manage new attributes on entities
Take advantage of custom attributes that can be added directly on your master data entities. In this latest release, you can now customize the data model of your entity types to add new entity attribute definitions, then edit individual entities to specify the attribute values.
Rather than relying on only record data to provide entity attribute values, the ability to specifically define entity attributes gives organizations the flexibility to store, capture, and manage digital twin attributes for each entity to better track behavior indicators, engagement preferences, and other key customer data points. Examples include:
Self-service attributes like communication preferences, privacy preferences, consents, etc.
Analytically derived attributes such as fraud indicators, segmentation indicators, buying behavior indicators, product mentions/social, churn indicators, next best action, and more
For more information about entity attributes, see Data concepts in IBM Match 360.
Real-time streaming of Match 360 data changes
Data consumers often are looking for the freshest data, in real time. Match 360 record and entity data changes are now propagated directly to downstream systems through a connected Apache Kafka server. Streaming ensures that your users and systems always have the freshest and most up-to-date master data.
For more information, see Streaming record and entity data changes. Master data streaming is available only through the IBM Match 360 API.
Additional recent capabilities from the last few launches include the Match 360 Connector to support relationship data, the ability to display Match 360 job logs from the common job console, glue thresholding, and more.