Is your MDM solution capable of scaling to today’s data sources, volumes, and complexity?
Standard MDM solutions are not built for high volumes of distributed, disparate data, that is generated by various applications and external sources.
Traditional MDM probabilistic matching doesn’t work well with siloed data sources. It misses connections, losing context, leads to decision-making inaccuracy, and leaves business value on the table. An ineffective MDM solution affects everything from customer experience to operational performance.
Your data is worth so much more
Enhance your existing MDM approach with contextual capabilities that bring data together from any source.
Contextual MDM enables you to:
- Connect data & add context
Use advanced Entity Resolution to create a joined-up view of data around people, businesses and addresses from across internal and external data sources. Add context by creating related parties and hierarchies automatically.
- Maintain the golden record
Automatically create and maintain golden records from a rich view of attributes from across linked records.
- Work dynamically
Not only batch – support real-time streaming of data in and out, so you can maintain up-to-date views and trigger processes in response to data changes.
- Enable your data team
Create the foundation for effective data and analytics, including graph network generation, visualization, and exploration.
reduction in records through de-duplication
Why choose Quantexa’s Contextual Master Data Management solution
Use best-in-class entity resolution
Find connections between customers and organizations across use cases that can’t be found using traditional matching approaches, even in the face of poor-quality or incomplete data.
Ensure a true single view across all systems
Contextual MDM effectively connects data into single views, so you can find all parties (such as customers, suppliers, agents) whether business or individual, and the roles they play in the organization.
Work in dynamic or batch modes
Support multiple MDM architecture styles and run entity resolution as regular batch, delta streaming to respond to source data changes or dynamically on-demand to support customer onboarding.
Maximize your ROI
Whether you are starting from scratch, or looking to optimize an existing MDM solution, Quantexa delivers value fast, with a modular approach that powers improvements to master data and delivers real digital business impact.
More solutions that help you drive value from your data
Enables a single platform to serve joined-up data across the enterprise. Separately ingested data sources can be dynamically queried as graphs or entities.
Entity Data Quality
Find duplicates and continuously improve data quality at the point where records are joined together. Measure and visualize to find the most impactful quality problems that need addressing and drive organizational behavior.
Save time and cut costs by fast-tracking your data migration, joining legacy data into a single view, and creating migration profiles.
Automatically create hierarchies – corporate, legal, credit, sales –using internal and external data sources. Use to maintain an accurate and up-to-date master record of your hierarchies.
Why use the Quantexa platform
Build once, use many, ingest to create a single view with networks
Apply your data to multiple use cases—without replicating data sets.
more accurate decisions
Use context to improve decision accuracy across the organization, find new opportunities and uncover risk.
Scale to billions of records
in batch or real time
Built on proven, scalable open source technologies like Hadoop, Spark and Elastic.
Future-proofed open architecture
Integrate seamlessly into your existing IT ecosystem, with flexible deployment options: native, or containerized for private and public cloud.
Ensure data transparency
Use explainable data linking, advanced AI and decision models for regulatory compliance.
Keep your data secure
Rely on granular security levels for dynamic control, with all activity audited.
Operationalize your data in a matter of months – not years.
Use entity resolution and data volume to overcome missing or poor quality data.
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