Master Data Management

Gain a complete, integrated view of your customer data, supplier data, product data, and other enterprise data

What Is Master Data Management?

Master data management (MDM) refers to the strategies that enterprises use for establishing authoritative sources of critical data so that stakeholders can obtain a single view of key entities.

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Master Data Management market will be worth $27B by 2020.

According to Markets and Markets research report.
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MDM Systems Are Great, But...

For many years, MDM has been a critical, integral part of the enterprise architecture. Your organization is probably using an MDM tool to manage customer data, product data, supplier data, or all of it. MDM tools are great for delivering a single view of your data or even the relationship between customer, product, or supplier entities. But when it comes to gaining a view into the various transactions that take place among these business entities, standalone MDM systems fall short because they do not store the associated transactions. Modern enterprises need a complete view of their master data that also includes transactions and interactions from social, streaming, and other forms of modern data.

Complete View of Master Data

A true, complete view of master data has three components:

  • A single view of the master data, for example knowing that “John Smith” and “J. Smith” are the same person.
  • A 360° view of the master data relationships, for example knowing that “John Smith” and “P. Smith” are part of the same family.
  • A view into each master data entity’s transactions and interactions, for example knowing that “John Smith” has called customer service three times in the last hour regarding a recent purchase.

Master data management systems are good at creating the first two views, but they do not store the associated transactional data.

 

By 2017, 89% of marketers expect customer experience to be their primary differentiator.

According to Gartner.
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Data Virtualization + MDM

MDM, when augmented with data virtualization, provides the complete view of the master data. The combination of technologies support three common usage patterns:

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Master Data Management for Analytics

In this scenario, the MDM system draws master data from disparate data sources, reconciles discrepancies, and creates golden records, and the data warehouse draws transactional data from a similar range of transactional sources. Data virtualization creates a unified view, composed of data drawn from both the MDM system and the data warehouse.

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Master Data Management for Operations

In this scenario, there is no data warehouse, as the data does not need to be stored for historical or analytical purposes. The data virtualization layer combines the master data from the MDM system with the associated transactional data drawn from the operational systems.

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Virtual Master Data Management

Traditional MDM systems, which store golden records in a separate database, often cannot be used in industries with heavy restrictions on data replication; industries such as healthcare and the public sector. In such cases, the data virtualization layer itself provides many of the functions of a traditional MDM system, while also creating a virtual view of the transactional data across myriad sources, as in the operationally focused architecture.

The Benefits of Using Data Virtualization with MDM

Data virtualization offers the following benefits, when augmented by a master data management system:

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A complete view of the master data,

including a single view of the customer, a 360° view of customer relationships, and a complete view of customer transactions and interactions.

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The ability to combine master data with any other data,

throughout the enterprise; data virtualization can connect to MDM systems and myriad other data sources.

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Real-time access

to the complete view, for any stakeholder in the organization.

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Reduced replication

and its associated costs and risks. Data virtualization provides data access without replication.

A short implementation timeframe;

a robust data virtualization layer can be developed and deployed in a matter of weeks.

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The only pure-play data virtualization product in the cloud

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