Guide to Contextual MDM: Put meaning back into your data

46% of organizations across the globe say their single view solutions can’t handle data lake volumes.


It’s critical for organizations to be able to accurately consolidate information about customers, suppliers, employees or associated parties – and to understand the relationships between them. But standard Master Data Management (MDM)solutions often struggle to bring together siloed data sources, resulting in painful consolidation and migration issues.


With a contextual approach to MDM, you can tackle the challenges of traditional MDM to empower a data-centric culture that drives business value.


Download this ebook to find out how to put context back into your data.


In this ebook, you’ll learn:

  • Why the limitations of traditional inflexible MDM systems result in a lack of business value
  • Ways to drive more value from your data with a contextual approach to master data management
  • What Contextual Decision Intelligence is and how it creates a holistic single view of master data
  • How to tackle data quality and data management challenges with a single entity view to ensure trustworthy and reliable data


The disconnected data disaster waiting to happen


As your company grows, your volume of data grows, too. But without a single view of master data, this data is being collected in siloes, resulting in:


  • Incomplete and outdated data records
  • Frustrated customer experiences
  • Laborious manual data gathering
  • Missed risk and revenue opportunities


To drive business value from your MDM systems, you need a solution that offers  better, more reliable outcomes.


Trust your records again with a better approach to Master Data Management


Context is the missing link. By applying context to your data, you can fill in the gaps on poor quality or incomplete records.


Download our free ebook to learn how you can create and maintain a rich view of master data, scale your data management with business growth – and safeguard your reputation.

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