MDM Terms in Use in the Gartner Hype Cycle

The latest Gartner Hype Cycle for Data and Analytics Governance and Master Data Management includes some of the MDM trends that have been touched here on the blog.

If we look at the post peak side, there are these five main variant – or family of variant – terms in motion:

  • Single domain MDM represented by the two most common domains being MDM of Product Data and MDM of Customer Data.
  • Multidomain MDM.
  • Cloud MDM.
  • Data Hub Strategy which I like to coin Extended MDM.
  • Interenterprise MDM, which before was coined Multienterprise MDM by Gartner and I like to coin Ecosystem Wide MDM.

It is also worth noticing that Gartner has dropped the term Multivector MDM from the hype cycle. This term never penetrated the market lingo.

Another term that is almost only used by Gartner is Application Data Management (ADM). That term is still in there.

The Future of Disruptive MDM is in the Cloud

Two recent posts on the Gartner blog is about databases in the cloud. The Future of Database Management Systems Is Cloud by Merv Adrian ponders why cloud is now the default platform for managing data and The Future of Database Management Systems Is Cloud by Donald Feinberg does the same. Well, the two posts are identical.

This will also mean that the default platform for Master Data Management (MDM) will be in the cloud. Add to that, that the other disruptive MDM trends also will work best in the cloud.

Disruptive MDM in the Cloud

  • We increasingly see Extended MDM Platforms that also handles reference data and big data. Both these data types are predominantly external in nature and therefore they are better collected, or even better connected, in the cloud.
  • Services for Artificial Intelligence (AI) and Master Data Management (MDM) is delivered by vendors as cloud solutions.
  • Encompassing IoT and MDM means collaboration between many parties and this is, with all the relationships to take care of, only possible with cloud platforms.
  • We will see several other use cases for business ecosystem wide cross company sharing of master data in what Gartner coins as Multienterprise MDM.

MDM Trend: Data as a Service

A recent post on this blog was called Five Disruptive MDM Trends. One of the trends mentioned herein is MDM in the cloud and one form of Master Data Management in the cloud in the picture is Data as a Service (DaaS).

DaaS within MDM

Using Data as a Service in the cloud within MDM solutions is a great way of ensuring data quality. You have access to real-time validation and enrichment of master data and you can also use third party and second party services in the on-boarding processes and then avoid typing in data with the unavoidable human errors that else is the most common root cause of data quality issues.

Some of the most common data services useful in MDM are:

Address Verification and Geocoding

When handling location data having a valid and standardized description of postal addresses and in many cases also a code that tells about the geographic position is crucial in MDM.

Postal address verification can either be exploited by a global service such as Loqate from GB Group or AddressDoctor, which is part of the Informatica offering. Alternatively, you can use national services that are better (but also narrowly) aligned with a given address format within a country and the specific extra services available in some countries.

Geocodes can either by latitude and longitude or flat map friendly geocoding systems such as UTM coordinates or WGS84 coordinates.

Business Directory Services

When handling party master data as B2B customers, suppliers and other business partners in is useful to validate and enrich the data with third party reference data and in some cases even onboard through these sources.

Again, there are global and local options. The most commonly used global is Dun & Bradstreet, who operates a database called WorldBase that holds business entities from all over the world in a uniform format and also provides data about the company family trees on a global basis. Alternatively, many countries have a national service provided by each government with formats and data elements specific to that country.

Citizen Directory Services

When handling party master data as B2C customers, employees and other personal data the third-party possibilities are sparser in general, naturally because of privacy concerns.

In Scandinavia, where I live, these data are available from public sources based on either our national ID or a correct name and address.

Data pools and Product Data Lake

When handling product master data and product information there are for some product groups and product attributes in some geographies data pools available. The most commonly used global service is GDSN from GS1.

Alternatively (or supplementary), for all other product groups, product attributes and digital assets and in all other geographies, you can use a service like the one I am working with and is called Product Data Lake.

Five Disruptive MDM Trends

As any other IT enabled discipline Master Data Management (MDM) continuously undergo a transformation while adopting emerging technologies. In the following I will focus on five trends that seen today seems to be disruptive:

Disruptive MDM

MDM in the Cloud

According to Gartner the share of cloud-based MDM deployment has increased from 19% in 2017 year to 24 % in 2018 and I am sure that number will increase again this year. But does it come as SaaS (Software as a Service), PaaS (Platform as a Service) or IaaS (Infrastructure as a Service)? And what about DaaS (Data as a Service). Learn more in the post MDM, Cloud, SaaS, PaaS, IaaS and DaaS.

Extended MDM Platforms

There is a tendency on the Master Data Management (MDM) market that solutions providers aim to deliver an extended MDM platform to underpin customer experience efforts. Such a platform will not only handle traditional master data, but also reference data, big data (as in data lakes) as well as linking to transactions. Learn more in the post Extended MDM Platforms.

AI and MDM

There is an interdependency between MDM and Artificial Intelligence (AI). AI and Machine Learning (ML) depends on data quality, that is sustained with MDM, as examined in the post Machine Learning, Artificial Intelligence and Data Quality. And you can use AI and ML to solve MDM issues as told in the post Six MDM, AI and ML Use Cases.

IoT and MDM

The scope of MDM will increase with the rise of Internet of Things (IoT) as reported in the post IoT and MDM. Probably we will see the highest maturity for that first in Industrial Internet of Things (IIoT), also referred to as Industry 4.0, as pondered in the post IIoT (or Industry 4.0) Will Mature Before IoT.

Ecosystem wide MDM

Doing Master Data Management (MDM) enterprise wide is hard enough. But it does not stop there. Increasingly every organization will be an integrated part of a business ecosystem where collaboration with business partners will be a part of digitalization and thus we will have a need for working on the same foundation around master data. Learn more in the post Multienterprise MDM.

The latest and hottest trends within MDM

Leading up to the Nordic Midsummer I am pleased to join Informatica and their co-hosts Capgemini and CGI at two morning seminars on how successful organizations can leverage data to drive their digital transformation, the needed data strategy and the urge to have a 360-view of data relationships and interactions.

My presentations will be an independent view on the question: What are the latest and hottest trends within Master Data Management?

In this session, I will give the audience a quick walk-through visiting some in vogue topics as MDM in the cloud, MDM for big data, embracing Internet of Things (IoT) within MDM, business ecosystem wide MDM and the impact of Artificial Intelligence (AI) on MDM.

The events will take place, and you can register to be there, as follows:

Infa Nordic morning seminars 2019

The Road Ahead for MDM

Even though that Master Data Management (MDM) has been around as a discipline for about 15 years now, there is still a lot of road to be covered for many organizations and for the discipline as a whole.

vestre kirkegaardSome of the topics I find to be the most promising visit points on this journey are cloud deployment of MDM solutions, inclusion of Artificial Intelligence (AI) in MDM and multienterprise MDM.

Cloud deployment of MDM has increased slowly but steadily over the recent years. Quite naturally the implementation of MDM in the cloud will follow the general adoption of cloud solutions deployed in each organization as master data is the glue between the data held in each application. Doing MDM in the cloud or not is, as with most things in life, not a simple question with a yes or no answer, as there are different deployment styles as examined in the post MDM, Cloud, SaaS, PaaS, IaaS and DaaS.

Inclusion of Artificial Intelligence (AI) and Machine Learning (ML) in the MDM discipline will, in my eyes, be one of the hottest topics in the years to come. MDM is not the easiest IT enabled discipline in which AI and ML can be applied. Handling master data has many manual processes today because it is highly interactive, and the needed day-to-day decisions requires much knowledge input. But we will get there step by step and we must start now as told in the post It is time to apply AI to MDM and PIM.

Multienterprise MDM is emerging as a necessity following the rise of digitalization. Increasingly every organization will be an integrated part of a business ecosystem where collaboration with business partners will be a part of digitalization and thus, we will have a need for working on the same foundation around master data. This theme was pondered in the post Share or be left out of business.

MDM, Cloud, SaaS, PaaS, IaaS and DaaS

A while ago the trend of having the possibility to deploy a Master Data Management (MDM) solution in the cloud was covered in the post The Rise of Cloud MDM.

The latest Gartner MDM Magic Quadrant report has some numbers on that trend as mentioned in the post Who Will Make the Next Disruption on the MDM Market? Cloud based deployment has increased from 19% in 2017 year to 24 % in 2018 among Gartner’s respondents. While the organizations included here are the larger ones, I will guestimate that the cloud portion of MDM implementations are higher among midsize and smaller organizations.

As mentioned in the Gartner report there are however some confusion about what a cloud MDM solution really is. Does it come as SaaS (Software as a Service), PaaS (Platform as a Service) or IaaS (Infrastructure as a Service)? In this spectrum the vendor will provide most things in a SaaS solution, lesser stuff as PaaS and only the ability for the software to be hosted somewhere out there as IaaS.

One “as a Service” component in relation to master data you could expect in SaaS, but not necessarily in IaaS, is DaaS (Data as a Service) as for example out-of-the-box address verification and business directory integration services. A common address verification service is the one from Loqate, while Informatica though have their own solution based on their AddressDoctor acquisition. The most common business directory provider is Dun & Bradstreet.

Else the difference follows the general difference between SaaS, PaaS and IaaS which is about what the organization has to do themselves (or through system integrators) around software updates, configuration, maintenance, monitoring and more.

On the brink to 2019 my guess is that we will see more MDM in the cloud next year as well as a movement from IaaS over PaaS to SaaS. This will include more DaaS covering more master data domains not at least in the product data space – a reason of being for the Product Data Lake service I am involved with.

Cloud MDM

The Rise of Cloud MDM

Cloud as a deployment method for Master Data Management (MDM) solutions is on the rise.

In the latest MDM vendor selection activities I am involved in cloud is not an absolute must but certainly the preferred deployment method.

The MDM vendor market is responding to that trend. Some of the new players offers purely cloud based solutions. In a recent post on this blog I wrote about Three Remarkable Observations about Reltio. The fourth will be that this is a cloud-based MDM (and more) solution – called Reltio Cloud.

Another example of going the cloud path is Riversand. Their new release is put forward as a cloud-native suite of Master Data Management solutions as told in an interview by Katie Fabiszak with CEO & Founder Upen Varanasi of Riversand. The interview is posted as a guest blog post on The Disruptive MDM List. The post is called Cloud multi-domain MDM as the foundation for Digital Transformation.

Cloud MDM



The Three MDM Ages

Master Data Management (MDM) is relatively new discipline. The future will prove what is was, but standing here in mid-2018 I see that we already had 2 ages and are now slowly proceeding into a 3rd age. These ages can be coined as:

  • Pre MDM,
  • Middle MDM and
  • High MDM


In these dark ages the term Master Data Management may have been used, but there were not any established discipline, methodologies, frameworks and technology solutions around that truly could count as MDM.

We had Customer Data Integration (CDI) around, we had Product Information Management (PIM) in the making and some of us were talking Data Quality Management – and that in practice being namely deduplication / data matching.

Middle MDM

MDM as Three Letter Acronym (TLA) emerged in the mid 00’s as told in the post Happy 10 Years Birthday MDM Solutions.

It was at that time Aaron Zornes changed his stage name from The Customer Data Integration Institute to The MDM Institute.

During this age many MDM solutions slowly but steadily have developed into multi-domain MDM solutions as reported over at the Disruptive MDM List in the blog post called 4 Vendor Paths to Multidomain MDM covering the road travelled by 10 vendors on the MDM market.

Most MDM solutions in the Middle MDM Age have been deployed on-premise

High MDM

We are now cruising into the High MDM Age. First and foremost a lot more organizations are now implementing MDM. Many new deployments are cloud based. New ways are tried out like encompassing more than master data in the same platform.

The jury is of course still out about what will be some main trends of the High MDM Age. My money is placed on what Gartner, the analyst firm, calls Multienterprise MDM as elaborated in the post Ecosystem Wide MDM.

MDM Ages.png