What is Master Data Management?

Master data management (MDM) is the process of making sure an organization is always working with, and making decisions based on, one version of current, ‘true’ data—often referred to as a "golden record."

Sounds simple, but in modern business environments, awash with constant streams of data, master data management may be one of the most complex business challenges. Ingesting data from diverse sources and presenting it as one constant, reliable source for verified, real-time information takes a combination of know-how, tools, and often a strategic partnership.

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6 Benefits of Master Data Management

Our increasingly digital world and the explosion of cloud technologies have moved data management to the forefront of the CIO’s potential headache list. Since so much of what happens during any given transaction his unseen tracking, sorting, and verifying background data can be a daunting task. But, effectively managed, here are six real impacts MDM can have on any organization.

1. Lower total cost of operation

Consider all the aspects of your business that produce and consume data:

  • All applications and their dependencies
  • Employee operations, from production to human resource events
  • Data stores, including hot (working) and cold (archival) information
  • Inventory schedules and ordering protocols
  • And more

A variation in the version or veracity of data from any of these sources can have a chain
reaction impact on all associated info, quickly impact operating expenses, and jeopardize the organization’s business. And it’s usually more of a problem than it initially appears. In one study:

  • Only 3% of the data quality scores could be rated “acceptable” using the loosest-possible standard.
  • On average, 47% of newly-created data records have at least one critical (e.g., work-impacting) error.

Trusted, current data has the inverse impact.

2. Lower architectural bloat through eliminated redundancies

Decreasing lost business isn’t the only way MDM impacts the bottom line. The cost of running and supporting network architecture—whether onsite, hybrid, or cloud-based—is directly impacted by the amount of resources used. This includes storage space, processing time, and network throughput.

By coalescing the data picture into one, trusted repository the need for individual sources to maintain their own resources is eliminated, and IT operational costs can be cut significantly.

3. Faster deliveries

MDM is a core consideration for modern development approaches like continuous delivery, DevOps, rugged DevOps, and other design architectures that require shared and reliable data.

With a trusted MDM data reservoir feeding development teams, apps and improvements speed through the delivery pipeline far faster. This means MDM discoveries unearthed today can potentially be put to work in software today, rather than after some extended review and recode process.

4. Simplified compliance

A major challenge in the modern digital business world is compliance, with regulations like HIPAA, PCI, CIPA, GDPR, and more regulatory frameworks rapidly changing required compliance measures. Compliance alone can be (and is, in larger organizations) a full-time pursuit.

MDM will take the grind out of performing mandatory compliance reports and audience by meeting all standards for verifiable, secure data integration.

5. Improved customer service

As the saying goes, time is money. In a digital world that moves at the speed of modern business this has never been more true, especially when it comes to your audience’s time. MDM provides a previously unavailable opportunity to interact with your customers during every step of the transaction process—and improve your performance based on real-time feedback—by eliminating inconsistencies and errors that impact product delivery—from first app interaction through shipping, delivery, and feedback.

6. 360-degree view

A modern, cloud-based MDM process creates a complete, real-time view of each customer. MDM creates a "golden record" that enables marketers to have up to date an accurate information for web personalization or prompts on Amazon.com of things that people bought along with a product you are considering.

7. Actionable business intelligence

Developing a clear and current picture of all business operations means decision makers can zoom in minutely on problem points, or pull back to a satellite view to see where national or global trends are impacting your business.

Since data is the foundation and life support of digital environments, the implications for MDM in any environment are as limitless as the data itself. If there is one modern technology that proves this daily it’s how organizations are attacking the challenging of MDM in the cloud.

Master Data Management in the Cloud: 4 Key Challenges

With the cloud, and the myriad opportunities it presents, comes a correspondingly large number of pitfalls that can occur with master data management in a public or hybrid cloud environment. Here are four critical challenge areas to address early, remembering that failure to plan is almost planning for failure:

  1. Account for wildly disparate data types. With all the devices, virtual and physical, involved with keeping customers engaged, no one data storage type will be sufficient for MDM. Structured and unstructured data will flow to and through an organization’s management tools, which must be flexible enough to accommodate it.
  2. Security! First, foremost, and always in modern digital environments, security must be the prime directive. If the advantages of MDM stem from a central source of truth from which an organization can operate, then inbound risks and threats targeting the source bring the ability to stop operations dead in their tracks. Hacks, malware, and even cyberansoming can and will be the result of MDM solutions that don’t keep security first.
  3. Governance. If MDM unleashes great potential power, the responsibility for managing it is equally monumental. Though most of the interactions used to present an MDM solution occur automatically in the background, it’s up to business leaders to decide what data is heavily weighted and how to interpret business intelligence. The right governance approach codifies not just the scope of the data but also who keeps/interprets it. This is the difference between just having a central source of truth, and putting it to powerful use.
  4. Expertise. Finding the right mix of experience and eagerness to learn quickly is probably the biggest MDM challenge many organizations face. Because cloud MDM is such an emergent field, most SMBs lack the internal personnel for crafting a holistic solution that’s customized to meet their needs. Training and development versus outsourcing is a decision to address early.

With these challenges in mind, consider which of the most frequently used designs best fits your needs. And just as importantly, your budget.

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Four Master Data Architecture Styles

No single MDM strategy fits every need. The advantage of the practice is its flexible, customizable approach to managing and governing your master data repository. That said, there are four general architectures into which initial MDM designs fall.

1. Registry Style MDM

In this approach, MDM works with abbreviated records, or “stubs,” that detail the data’s source, current location, and more. Registry is the fastest and least expensive architecture to deploy because it minimizes the amount of data actually moving through MDM tools, instead consolidating stubs into a working repository.

The disadvantages of registry include higher latency inherent in gathering and comparing master records with remote device information. Additionally, registry is a one-way collection, and changes made at the master level do not propagate to remote sources, resulting in inconsistencies between master and remote.

2. Consolidated Style MDM

A consolidated architecture is similar to a registry, but actually moves data from sources to the master repository.

This approach is popular in environments where latency is expected, and consolidation generally takes place during scheduled batch process windows. However, as with the registry style, data in the master repository is not synchronized with downstream sources.

3. Coexistent Style MDM

This architectural approach takes consolidated MDM a step further and adds the critical step of synchronizing master data back down to the sources, creating a master record that ‘coexists’ in both the prime repository and at the individual system level.

This is a more complex approach and also comes with high latency, as data needs to be collected and disseminated back downstream via separate batch processes. This architecture is common with small and mid-sized companies that can afford to synchronize master data multiple times per defined period.

4. Transactional Style MDM

The most complete architectural approach, transactional style MDM, is also the most costly in terms of overhead. Master data is migrated from the sources to the master repository, where it is processed, cleaned, standardized, then returned to the sources.

This style reduces latency by direct coordination between master and source, and comes with the advantage of enforcing data governance rules across the enterprise. However, it requires a high level of expertise and the right tools for custom coding to ensure proper flow and prevent flawed data from propagating across the environment.

It’s not uncommon for organizations to begin with one MDM architecture then evolve into another. The measure of a successful MDM build is the efficiency, speed, and consistency with which master data is moved and stored.

Master Data Management and Service-Oriented Architecture

MDM takes on a new significance—and power—in the cloud through its interoperation with service-oriented architecture (SOA). When almost everything, including infrastructure, is virtualized, the costs of inconsistent or corrupt data can be crippling. MDM provides SOAs, including Internet as a Service (IaaS), to work from one source of truth, making enterprise-wide change consistency achievable in near real-time.

A core challenge of MDM in SOA is a data governance approach that standardizes data structure and rules between the repository and the host of remote systems, services, and software. Coordinating a working protocol for exchanging and overwriting data between different systems can be a daunting challenge for existing IT staff. That’s where partnering with a trusted expert simplifies the MDM picture.

Taking the Next Steps with MDM

Every day, MDM in the cloud is changing the speed and reach of business. Achieving a master data management solution allows organizations to close the space between delivered products and users to near real-time, turning data environments into almost living organisms that react and respond to modern business world.

Learn more about MDM and start putting its power to use today!

| Last Updated: February 22nd, 2018