What is Master Data Management?

A Definition of Master Data Management (MDM)

Master data management (MDM) is an approach to reducing data redundancy by maintaining a definitive "record of truth," or master file, for critical data in order to supply a single source as a reference. Ideally, MDM organizes data sharing among multiple applications or departments.

It Starts with Data Integration

It's common for organizations to have duplicate information on different systems. For example, customer information could be stored in both a CRM and accounting system:

While some data in both systems is identical, some is similar but not the same. 

With small organizations, there usually isn't an issue keeping just a few systems up to date. The process of keeping data up to date between disparate systems is called Data Integration (DI).

As organizations bring more and more systems online, their business data typically gets increasingly duplicated and the problem of keeping all of the systems up to date becomes problematic. For example, imagine a delivery service that stores information about its customers in several systems:

As customer information changes over time (i.e. customer address or phone number), keeping all the systems up to date becomes exponentially more difficult.

Considering the diagram above:

• Where is the truth?

A customer's email address would be stored on several systems and there may be conflicting values. If this is the case, which system holds the true/correct value?

• Which system gets notified of a change and what data elements do other systems need? 

If all systems need to be updated, then each system needs to know how to transform the data to be consumed by each of the other systems. This requires programming many transformations. In an extreme case, the example above could take five transformations for each of the six systems, totaling 30 transformation modules or adaptors.

Note: An adaptor is software located within a system that connects and shares data through the YOUnite Data Hub. The adaptor focuses on Extract, Transform, and Load (ETL): ensuring any system "outbound data" meets defined format requirements and then gets transformed into "inbound data" format that another system requires. 

• Are changes handled in real time or in batch?

The easiest and most common change handling is via batch updates. However, latency between batch updates may cause business process issues.  

• How is DI handled?

The onus of transferring data between systems can become a daunting task. While some applications have built-in adaptors to handle transformations, these generally handle only a subset of the required data. Where the built-in adaptors fall short or don't exist, the organization may end up spending resources developing "one-off" adaptors to meet the ongoing transformation need. 

• How does the organization manage access to the data?

Using the example above, the Warehouse Management system should get access to only a subset of the customer data for security reasons. And it shouldn't get any level of access to the Credit Card Processing system. The term Data Governance is used to describe managing data access.

The problem doesn't end with just the customer data. Other data such as product, inventory, and employee data may need to be kept up to date on several systems as well:

In Master Data Management, the set of fields or properties that define a set of data (e.g. Customer) is called a data domain. 

Migrating to Master Data Management

Master data management (MDM) solves the problem of keeping interrelated systems up to date by creating a separate system where data domains (or domains) are defined for all systems inside the organization. The domains provide neutral data formats or schemas for all systems.

The data for a YOUnite domain can be stored either:

1. In the YOUnite data store or,
2. Through adaptors, it can connect to the organization's systems without actually storing the data; this is called federated MDM.

The latest version of a record is called the  Data Record. Part of the responsibility of Data Governance is to define where the records of truth or Master Data is stored

Using the example of our delivery service:

1. If the customer domain is stored in the YOUnite data store, the customer data record is stored by YOUnite and can be retrieved, in whole or in part, by applications that have appropriate access.
2. If the customer domain is  federated, then the customer record is NOT stored inside of YOUnite but is created in real-time by referencing the elements (or properties) as they reside inside the various systems.

YOUnite's governance model can manage who can access the data so in the federated example, perhaps the Warehouse Management system only has access to data stored in the Distribution and CRM systems. but the Accounting System has access to all systems. When the Warehouse Division looks up the data record for its customer the Acme Company it may get a different result than Accounting Division since the Accounting Division has access or scope to Acme Company's information on all systems. 

Master data management is the process of determining where the master data is stored and managing who has read, write, update and delete. With YOUnite MDM master data can be stored in the YOUnite data store or in one or more systems connected to YOUnite in the federated model. Many systems may hold similar data but generally the organization as a whole decides which system(s) hold the master data and subsequently the master data records. Note that with YOUnite/s federated model, different groups inside of an organization can designate which system holds the master data.

Data Records vs Master Data Records

Data records are stored in many systems connected to YOUnite and can be stored in the YOUnite data store. Master data is a process performed by the organization's data governance in establishing which of these systems contain the master data for a given data domain.  Its not always necessary or appropriate to access the organization's master data so many data access requests are for data records that may or may not contain master data.   However, a feature of YOUnite is to propagate changes from a system that contains master data to others in the YOUnite eco-system on a permission appropriate basis.

Reviewing New Terms

Several terms have been introduced and it may be helpful to review them before moving on:

• Data Integration (DI) The process of transforming and transferring data from one system to another.
• Adaptor Applications, modules or some software or hardware component that transforms data from one format to the other so that the data can be consumed by another system.
• Data Governance Managing who accesses certain data sets based on role, application, etc.
• Data Domain (Domain) A set of fields or properties that define a set of data (i.e. "Customer").
• Master Data Management (MDM) An approach to reducing data redundancy across systems by maintaining a master file for critical data.
• Data Record
• Master Data Record (MDR) The master or golden version of a record (for a customer, for example).
• YOUnite Data Store  Whereby the latest change to a record is saved inside of YOUnite (in the YOUnite MDM domain). From http://www.oracle.com/technetwork/articles/soa/ind-soa-mdm-2090170.html: MDM with a central database or central business applications.
• Federated MDM Whereby the latest change to a record is noted in one of the organization's systems without actually storing the data centrally (in the YOUnite MDM domain). From http://www.oracle.com/technetwork/articles/soa/ind-soa-mdm-2090170.html: MDM with distributed data and a central directory.
• Scope The defined access limit to MDM data for any given system, application, or role.

Further Reading

An good source for more MDM background  is Mark Allen and Cervo Dalton's Multi-domain Master Data Management: Advanced MDM and Data Governance in Practice. Waltham, MA: Morgan Kaufmann, 2015. (ISBM 978-0-12-800835-5).

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