The Basics of Master Data Management (MDM), Part 1
Part one of a two-part series.
"What is Master Data Management (MDM)?"
This is the question we set out to answer when we launched in early 2021 Informatica’s Back to Basics webinar series focused on mastering data. The idea of building a series of webinars that would answer questions about different aspects of MDM emerged from our conversations with industry analysts - it's the question that remains top of mind during their discussions with clients searching for a “single version of truth."
To find the answer to that question, I sat down with experts from Informatica and set out to address the 10 most frequently asked questions about mastering data. In the process, we created a Master Data Management 101.
- What does a master data management tool do?
- How does reference data vary from master data?
- Why is it necessary to master customer data?
- How does MDM complement a Customer Data Platform (CDP)?
- What are the trends in master data management?
- What are MDM best practices when implementing a solution?
- What is master data governance?
- What are challenges of supplier data management?
- Why is product information management needed?
- What should I consider for cloud MDM?
Our goal for this series is to simplify the basic concepts of master data management for everyone.
For those who are new to MDM, we want this series to shed some light on the value and purpose of MDM.
And if you already know about MDM, we hope you walk away with a few ideas that can help you communicate what MDM is and how it can help your organization reach your desired business outcomes faster (particularly with a business user or non-technical audience).
Now that all 10 episodes in the series are available on demand, we thought it would be informative to take a quick review of the highlights from the first five episodes (highlights from episodes 6 – 10 can be found here):
Episode 1: What does a master data management tool do?
A comparison I’ve often used is that the outcome of an MDM tool is similar to the household use of an atomic clock, but obviously with data instead of time. With analog or digital home clocks, the time slows down or speeds up. When this happens, if you have many clocks in your home, the time is often in conflict across them. Each clock will need to be manually reset to the current time; much like the quality of data within a system, if not managed, will need to be corrected when it begins to become inaccurate.
But there are household clocks—our mobile phones included—that sync centrally with an atomic clock. An atomic clock is always accurate, and we trust the time we see on our iPhones, even as we move across different time zones or travel to different countries.
In this first webinar, my colleague Prash Chandramohan (@MDMGeek), does a fantastic job walking through the concepts of what master data is and is not, typical use cases for MDM, and the critical capabilities of an MDM solution. If you are looking to learn about MDM or explain MDM to someone, this episode is a great resource.
Episode 2: How does reference data vary from master data?
It’s been estimated that anywhere between 20% to 50% of the tables in a database house reference data. A subset of master data, reference data helps with classification and categorization. Continuing the time analogy, reference data can be thought of as the lookup values of time that can be cross-referenced (such as AM or PM), or time zones(GMT, UTC, or Zulu time).
But more commonly, reference data is thought of as internal or external data standards that provide the allowed values for those fields. They can be units of measure, country codes, fixed conversion rates, G/L or accounting codes, or industry codes—zip codes, healthcare codes, city codes, currency conversion rates, and so on.
At the first MDM conference I went to 7 years ago, someone asked me about the difference between MDM and reference data, and that hasn’t changed: there remains a lot of confusion about what reference data is, and the best way to identify and manage it. For this webinar, I’m again joined by Prash Chandramohan as we explain reference data management and its value.
Episode 3: Why is it necessary to master customer data?
The most common data domain that is mastered, customer data exists across many different systems and is often fragmented, containing only the data that is necessary for a specific purpose. Bringing together data that’s scattered across these systems provides that 360-degree view of the customer.
But customer data is messy, and often messier than you might think. Customer data—names, addresses, telephone numbers—changes often. And, as custodians of that data, it also needs to be safeguarded.
Since a customer 360 is an essential and foundational component of a customer experience initiative, customer data must be governed, mastered, protected. In this webinar on customer data management, Gina Bulotovic from our pre-sales team walks through the steps and importance of mastering customer data.
Episode 4: How does MDM complement a CDP?
A Customer Data Platform (CDP) is a marketer-managed system that creates a persistent, unified customer database that is accessible to other systems. It is used departmentally for unifying customer profiles, audience segmentation, and predictive analytics so that organizations can take timely and relevant action to improve customer outreach. CDPs improve marketing, sales, and service execution through deeper insights
As with reference and master data, there is a lot of confusion about customer master data management and Customer Data Platforms. As many master data management systems are being extended with CDPs, I’ll be joined by Glenn Riedel, MDM Sales Specialist, for an episode about customer data and CDPs. We’ll offer some clarity on the overlap and differences between MDM and CDPs and take a deeper dive into Informatica’s perspective on the value and requirements of a CDP.
Episode 5: What are the trends in master data management?
Introduced more than 25 years ago, master data management continues to evolve from its origins in customer data integration and product information management. After all, data is constantly evolving—and this evolution creates new sources, types, and needs for data within an organization.
And as MDM becomes more critical for driving business success, the more important it becomes to be aware of new technologies and methodologies for capturing, managing, and using master data. AI/ML, cloud, federated architectures, inter-enterprise sharing, global deployment, data platform solutions, and other modern MDM capabilities are driving the next iteration of MDM solutions.
In this fifth episode of our ten-episode series, I’m joined again by Prash Chandramohan, to discuss these 8 trends and the impact on MDM solutions.
These webinars have been well-received and are among the most highly rated from the year. If you’d like to learn more and explore these topics, I encourage you to register for the series. To register for all the webinars in the first half of the series, be sure to click here.
We’re looking forward to 2022. We really hope you enjoy these educational webinars – and feel free to share with your colleagues.
