MDM License Distribution

Some of the hard facts presented in the Gartner Magic Quadrant for Master Data Management (MDM) Solutions is how the vendor licenses are distributed between the various master data domains. You can find these figures from the previous quadrant in the post Counting MDM Licenses.

The Latest MDM Magic Quadrant also includes these numbers. In order to highlight how the vendors have different profiles, let us concentrate on the innovative solutions registered on The Disruptive MDM / PIM / DQM List.

MDM License Distribution
Source: Gartner

The above figure shows the three domains where the vendor has sold the most licenses and how many customers who are handling multiple domains.

Contentserv is coming from a strong position in the Product Information Management (PIM) market and still have the vast part of licenses attached to product master data.

Enterworks is also coming from the PIM space and are with their ecosystem wide (or interenterprise as Gartner says) approach building up the multidomain grip through encompassing supplier master data.

Informatica is covering all domains with their suite of 360 solutions and have a good portion of customers doing multidomain MDM.

Reltio does cover all domains but are increasingly focusing on the customer domain with their connected customer 360 offering that encompasses all customer data.

Riversand is another vendor coming from the PIM space that is now growing into the multidomain MDM sphere with their new cloud-native platform.

Semarchy is with their Intelligent Data Hub concept going beyond multidomain MDM into handling more kinds of data as reference data and critical application data.

This diversity means that you cannot just use a generic ranking as presented in the magic quadrant when selecting the best fit solution for your intended solution. You must make a tailored selection.

What has Changed with the Gartner MDM Magic Quadrant?

The latest Gartner Magic Quadrant for Master Data Management (MDM) Solutions was published last month.

There was not much movement in the vendors positioning compared to last year. Only, as told in the post The Latest MDM Magic Quadrant, Informatica went further top-right with their suite of 360 solutions and Semarchy went up and above SAP MDG as the top challenger.

Semarchy was also among the ones with the highest revenue growth, so their Intelligent Data Hub approach seems to work pretty well both technically and commercially.

The growth race had Reltio as the winner as reported in the post Growth on the MDM Market.

Some years ago Gartner dropped mentioning other MDM vendors than the ones meeting the quadrant criteria. This year a small section of those has returned as Honorable Mentions. These are Magnitude Software, who recently has returned to branding their MDM offering as Kalido, Software AG, PiLog. Unidata, Boomi – the integration-oriented solution from Dell, and the data quality specialist Syncsort – who has acquired Pitney Bowes’ software and data business.

The market overview section was smaller and less informative this year. In here Gartner confirms that digitalization remains the most significant driver for growth in the MDM market and that privacy regulations also continue to drive exploration of MDM initiatives.

You can, against a minimal of personal info, download the report from Semarchy here.

MDM MQ change

 

The State of the PIM Market Going into the Twenty-Twenties

I had the pleasure of working with the folks at Dynamicweb PIM, one of the new innovative Product Information Management (PIM) solutions, on a white paper that examines the PIM market here on the doorstep to the 20s.

A key observation is that unlike the Master Data Management (MDM) market, smaller vendors in total have a significant share of what can be seen as the PIM market. Even the largest MDM / PIM vendors do not have a significant share of the PIM market as PIM solutions are used in many midsize companies, where the larger solutions do not have a relevant cost / benefit ratio.

There is no sign of massive consolidation on the PIM market. The largest vendors do not make many acquisitions that increase their market share, nor do they seem to grow organically more than the PIM market in total. Consequently, the PIM market is in no way dominated by a few large vendors as we see it on the CRM market, where Salesforce.com and Microsoft CRM have a predominant market share stretching into the midsize sector.

Therefore, organizations on the look for a PIM solution have a widening range of options to choose from where factors as the organization size, geographic reach, industry affiliation and current IT landscape are determining what is the objectively best choice of PIM solution.

You can download the state of PIM white paper here from the Dynamicweb site.

PIM 2020

Take Part in State of Data 2020

KDR Recruitment is a data management recruitment company and one of those rare recruitment agencies that genuinely express an interest in the disciplines covered.

This is manifested in among other things a yearly survey and report about the state of data that also was touched on this blog five years ago in the post Integration Matters.

This year the surveyed topics include for example how to use data analysis, new skills needed and the most effective ways to improve data quality. You can participate with your experience and observations here at State of Data 2020.

KDR state of data 2020

Growth on the MDM Market

As reported yesterday a new Gartner MDM Magic Quadrant is out.

MDM Growth
MDM license and maintenance revenue in M USD and growth %. Source: Gartner.

While the change in positions is limited the change in market share is more significant, if we look at the license and maintenance revenue estimates provided by Gartner. The numbers included in the new quadrant published in January 2020 are 2018 estimates. The figure here compares those numbers to the 2017 numbers included in the previous quadrant published in December 2018.

The trend is that the largest providers are not growing as fast as some of the midsize providers, where Reltio, Ataccama and Semarchy are going in the fast lane.

If any of the solution providers have some 2019 updates, please comment here.

The Latest MDM Magic Quadrant

With some delay the latest Gartner Magic Quadrant for Master Data Management Solutions has now been published and has began surfacing on the vendor websites.

I will get back with more take away. As a starter, a short look at the movements in the quadrant, where it can be observed that:

  • Informatica is heading towards the top-right corner
  • TIBCO Software has defended the second place held by Orchestra Networks following the take over
  • Semarchy is up in third position following the high jump into the challengers quadrant last year

MDM MQ 18 to 19Bigger picture here.

Download the report from Semarchy here or Informatica here.

Most Visited Posts in 2019

Another year has gone as this blog is well into the 11th year of being online.

The 3 most visited blog posts this year were:

AI iconData Matching, Machine Learning and Artificial Intelligence: A post from November 2018 about how AI and data matching has been combined for many years and how this theme has got a revival with the general rise of Artificial Intelligence (AI).

Data ManagementA Data Management Mind Map: A post with not so much text but instead an image reflecting how some of most addressed data management disciplines can be mind-mapped.

Forrester vs GartnerForrester vs Gartner on MDM/PIM: A post about how the two most acknowledged analyst firms rate the vendors on the Master Data Management (MDM) / Product Information Management (PIM) market. Early next year we can expect a new MDM Magic Quadrant from Gartner, so let us see how things look then.

Looking forward to what the next year – and decade – brings in the data quality, MDM and PIM space and to write some posts about it.

Happy New Year.

Four Themes That Will Take MDM Beyond MDM as We Have Known It

The Master Data Management (MDM) discipline is emerging. A certain trend is that MDM solutions will grow beyond handling traditional master data entities and encompass other kinds of data and more capabilities that can be used for other kinds of data as well.

Semarchy XDMThis include:

  • Utilizing data discovery to explore data sources with master data, reference data, critical application data and other kinds of data as described in the post How Data Discovery Makes a Data Hub More Valuable.
  • Governing the full set of data that needs to be governed as examined in the post Maturing RDM, MDM and ADM With Collaborative Data Governance.
  • Building a data hub that encompass the right representation of data that needs to be shared enterprise wide and even business ecosystem wide as explained in the post Why Flexible Data Models are Crucial in Data Sharing.
  • Measuring data quality in conjunction with general key performance indicators in dashboards that besides master data also embraces other internal and external sources as for example aggregated data from data warehouses and data lakes.

These themes were also covered in a webinar I presented with Semarchy last month. Watch the webinar The Intelligent Data Hub: MDM and Beyond.

The PIM Market as Seen by IDC

The are not so many reliable market reports dealing with the Product Information Management (PIM) market. So, it is interesting that a new one from an acknowledged source has arrived.

IDC has published their first PIM MarketSpace report. As stated in the report: “Historically, PIM has been closely associated with master data management (MDM) software, which provides a central source of truth for product data. However, MDM applications, as they were originally conceived, have some shortcomings when it comes to supporting today’s digital commerce requirements.”

When ranking the vendors, IDC reached this result:

IDC Marketscape PIM 2019 20

You can, against your personal data, get a partial report from Akeneo and Salsify.

PS: You can learn more about some of the other solutions on The Disruptive MDM /PIM /DQM List.

The Two Data Quality Definitions

If you search on Google for “data quality” you will find the ever-recurring discussion on how we can define data quality.

This is also true for the top ranked none sponsored articles as the Wikipedia page on data quality and an article from Profisee called Data Quality – What, Why, How, 10 Best Practices & More!

The two predominant definitions are that data is of high quality if the data:

  • Is fit for the intended purpose of use.
  • Correctly represent the real-world construct that the data describes.

Personally, I think it is a balance.

Data Quality Definition

In theory I am on the right side. This is probably because I most often work with master data, where the same data have multiple purposes.

However, as a consultant helping organizations with getting the funding in place and getting the data quality improvement done within time and budget I do end up on the other side.

What about you? Where do you stand in this question?