Looking for the Right MDM / PIM / DQM Implementation Partner

The Disruptive MDM / PIM / DQM List has been running for a couple of years and is now a list of 15 of some of the most innovative and forward looking solutions on the Master Data Management (MDM), Product Information Management (PIM) and Data Quality Management (DQM) market.

The list can be seen as an online MDM / PIM / DQM conference:

The Online MDM PIM DQM Conference

In these times when offline MDM / PIM / DQM conferences are cancelled, I thought it might be useful to uncover if there is an interest among implementation partners in this space to join the list on an adjacent list on the site covering these services, as it besides choosing the right solution is equally important to choose the right implementation partner.

So, if you as an implementation partner are interested, you can register here.

Alternatively, give me a shout here:

The Latest Disruptive MDM Entry: Unidata

Gartner has restarted mentioning some of the Master Data Management (MDM) solutions not (yet) meeting the threshold criteria for the MDM Magic Quadrant as reported in the post What has Changed with the Gartner MDM Magic Quadrant?

One of the solutions in this tiny crowd is Unidata.

The sister site to this blog is The Disruptive MDM / PIM / DQM List. So very timely it is good to be able to present Unidata on this site as well – and providing some more information than Gartner do.

An interesting fact about Unidata is that the core of its data management platform is under an open license which is “part of the company’s strategy and mission to form a community of experts in the field of data management and is aimed at developing the industry as a whole”.

Learn more about Unidata here.Unidata image

10 MDMish TLAs You Should Know

TLA stands for Three Letter Acronym. The world is full of TLAs. The IT world is indeed full of TLAs. The Data Management world is also full of TLAs. Here are 10 TLAs from the data management space that surrounds Master Data Management:

Def MDM

MDM: Master Data Management can be defined as a comprehensive method of enabling an enterprise to link all of its critical data to a common point of reference. When properly done, MDM improves data quality, while streamlining data sharing across personnel and departments. In addition, MDM can facilitate computing in multiple system architectures, platforms and applications. You can find the source of this definition and 3 other – somewhat similar – definitions in the post 4 MDM Definitions: Which One is the Best?

The most addressed master data domains are parties encompassing customer, supplier and employee roles, things as products and assets as well as location.

Def PIM

PIM: Product Information Management is a discipline that overlaps MDM. In PIM you focus on product master data and a long tail of specific product information – often called attributes – that is needed for a given classification of products.

Furthermore, PIM deals with how products are related as for example accessories, replacements and spare parts as well as the cross-sell and up-sell opportunities there are between products.

PIM also handles how products have digital assets attached.

This data is used in omni-channel scenarios to ensure that the products you sell are presented with consistent, complete and accurate data. Learn more in the post Five Product Information Management Core Aspects.

Def DAM

DAM: Digital Asset Management is about handling extended features of digital assets often related to master data and especially product information. The digital assets can be photos of people and places, product images, line drawings, certificates, brochures, videos and much more.

Within DAM you are able to apply tags to digital assets, you can convert between the various file formats and you can keep track of the different format variants – like sizes – of a digital asset.

You can learn more about how these first 3 mentioned TLAs are connected in the post How MDM, PIM and DAM Stick Together.

Def DQM

DQM: Data Quality Management is dealing with assessing and improving the quality of data in order to make your business more competitive. It is about making data fit for the intended (multiple) purpose(s) of use which most often is best to achieved by real-world alignment. It is about people, processes and technology. When it comes to technology there are different implementations as told in the post DQM Tools In and Around MDM Tools.

The most used technologies in data quality management are data profiling, that measures what the data stored looks like, and data matching, that links data records that do have the same values, but describes the same real world entity.

Def RDM

RDM: Reference Data Management encompass those typically smaller lists of data records that are referenced by master data and transaction data. These lists do not change often. They tend to be externally defined but can also be internally defined within each organization.

Examples of reference data are hierarchies of location references as countries, states/provinces and postal codes, different industry code systems and how they map and the many product classification systems to choose from.

Learn more in the post What is Reference Data Management (RDM)?

Def CDI

CDI: Customer Data Integration is considered as the predecessor to MDM, as the first MDMish solutions focused on federating customer master data handled in multiple applications across the IT landscape within an enterprise.

The most addressed sources with customer master data are CRM applications and ERP applications, however most enterprises have several of other applications where customer master data are captured.

You may ask: What Happened to CDI?

Def CDP

CDP: Customer Data Platform is an emerging kind of solution that provides a centralized registry of all data related to parties regarded as (prospective) customers at an enterprise.

In that way CDP goes far beyond customer master data by encompassing traditional transaction data related to customers and the emerging big data sources too.

Right now, we see such solutions coming both from MDM solution vendors and CRM vendors as reported in the post CDP: Is that part of CRM or MDM?

Def ADM

ADM: Application Data Management is about not just master data, but all critical data that is somehow shared between personel and departments. In that sense MDM covers all master within an organization and ADM covers all (critical) data in a given application and the intersection is looking at master data in a given application.

ADM is an emerging term and we still do not have a well-defined market – if there ever will be one – as examined in the post Who are the ADM Solution Providers?

Def PXM

PXM: Product eXperience Management is another emerging term that describes a trend to distance some PIM solutions from the MDM flavour and more towards digital experience / customer experience themes.

In PXM the focus is on personalization of product information, Search Ingine Optimization and exploiting Artificial Intelligence (AI) in those quests.

Read more about it in the post What is PxM?

Def PDS

PDS: Product Data Syndication connects MDM, PIM (and other) solutions at each trading partner with each other within business ecosystems. As this is an area where we can expect future growth along with the digital transformation theme, you can get the details in the post What is Product Data Syndication (PDS)?

One example of a PDS service is the Product Data Lake solution I have been working with during the last couple of year. Learn why this PDS service is needed here.

Why Flexible Data Models are Crucial in Data Sharing

Master data and reference data are two types of data that are shared enterprise wide and even in the wider business ecosystem where your company operates.

In your organization and business ecosystem the data that is shared is basically held in applications like ERP and CRM solutions that have come with a data model provided by the solution vendor. These data models are built to facilitate the operations that is supported by each of these applications and is a data model that must suite every kind of organization.

A core reason of being for a Master Data Management (MDM) solution is to provide a data store where master data is represented in a way that reflects the business model of your organization. This data store serves many purposes as for example being a data integration hub and the place where the results of data quality improvements (eg de-duplication) are stored.

Data model

Such a data hub can go beyond master data entities and represent reference data and critical application data that is shared across your organization and the wider business ecosystem within a given industry.

Learn more about flexible data models in a data hub context in the Semarchy whitepaper authored by me and titled The Intelligent Data Hub: Taking MDM to the Next Level.

Maturing RDM, MDM and ADM With Collaborative Data Governance

Data Governance and Master Data Management (MDM) are overlapping disciplines. When embarking on a data governance initiative you may encounter some difficulties in what belongs to the data governance side and what belongs to the master data side. One of the challenges is that data governance should also encompass other data than master data. The most common examples are reference data and other critical application data than master data.

So, while you may get coverage for setting up data stewardship, processes and the data platform for master data in a traditional MDM tool, other important aspects as the data governance related to Reference Data Management (RDM) and Application Data Management (ADM) may have to be implemented separately.

This calls for taking the MDM solution to the next level by encompassing reference data and application data as well. In that way essential data governance definition components as a business glossary, data policies and data standards as well as the enforcement components through data stewardship can be implemented in a collaborative way:

RDM MDM ADM

In this case the MDM platform will be extended to be an intelligent data hub. In collaboration with FX Nicolas I will be presenting such a solution in a webinar hosted by Semarchy. The webinar goes live Wednesday 13th November at 5pm CET / 11am ET. Register here on Intelligent Data Hub: MDM and Beyond.

MDM, PIM, DAM and 7 More Data Management TLAs

What is CDI (in a data management context)? What does PDS stand for? And what about RDM?

Well, here is an under 2 minutes silent video going through what 10 common Three Letter Acronyms in the data management world is:

Read more about the Three Letter Acronyms in the post 10 Data Management TLAs You Should Know.

Learn more about some of the best solutions in this space on The Disruptive MDM / PIM / DQM List.

10 Data Management TLAs You Should Know

TLA stands for Three Letter Acronym. The world is full of TLAs. The IT world is full of TLAs. The Data Management world is full of TLAs. Here are 10 TLAs from the data management world that have been mentioned a lot of times on this blog and the sister blog over at The Disruptive MDM / PIM / DQM List:

MDM = Master Data Management can be defined as a comprehensive method of enabling an enterprise to link all of its critical data to a common point of reference. When properly done, MDM improves data quality, while streamlining data sharing across personnel and departments. In addition, MDM can facilitate computing in multiple system architectures, platforms and applications. You can find the source of this definition and 3 other – somewhat similar – definitions in the post 4 MDM Definitions: Which One is the Best?

PIM = Product Information Management is a discipline that overlaps MDM. In PIM you focus on product master data and a long tail of specific product information related to each given classification of products. This data is used in omni-channel scenarios to ensure that the products you sell are presented with consistent, complete and accurate data. Learn more in the post Five Product Information Management Core Aspects.

DAM = Digital Asset Management is about handling rich media files often related to master data and especially product information. The digital assets can be photos of people and places, product images, line drawings, brochures, videos and much more. You can learn more about how these first 3 mentioned TLAs are connected in the post How MDM, PIM and DAM Stick Together.

DQM = Data Quality Management is dealing with assessing and improving the quality of data in order to make your business more competitive. It is about making data fit for the intended (multiple) purpose(s) of use which most often is best to achieved by real-world alignment. It is about people, processes and technology. When it comes to technology there are different implementations as told in the post DQM Tools In and Around MDM Tools.

RDM = Reference Data Management encompass those typically smaller lists of data records that are referenced by master data and transaction data. These lists do not change often. They tend to be externally defined but can also be internally defined within each organization. Learn more in the post What is Reference Data Management (RDM)?

10 TLA show

CDI = Customer Data Integration, which is considered as the predecessor to MDM, as the first MDMish solutions focussed on federating customer master data handled in multiple applications across the IT landscape within an enterprise. You may ask: What Happened to CDI?

CDP = Customer Data Platform is an emerging kind of solution that provides a centralized registry of all data related to parties regarded as (prospective) customers at an enterprise. Right now, we see such solutions coming both from MDM solution vendors and CRM vendors as reported in the post CDP: Is that part of CRM or MDM?

ADM = Application Data Management, which is about not just master data, but all critical data however limited to a single (suite of) application(s) at the time. ADM is an emerging term and we still do not have a well-defined market as examined in the post Who are the ADM Solution Providers?

PXM = Product eXperience Management is another emerging term that describes a trend to distance some PIM solutions from the MDM flavour and more towards digital experience / customer experience themes. Read more about it in the post What is PxM?

PDS = Product Data Syndication, which connects MDM, PIM (and other) solutions at each trading partner with each other within business ecosystems. As this is an area where we can expect future growth along with the digital transformation theme, you can get the details in the post What is Product Data Syndication (PDS)?

If a country list is that hard, MDM is really hard

A twitter post directing to an article with the title Make the Right Choice Using the Right Criteria: A Checklist for Exploring MDM Solutions and Capabilities made me curious and got my click.

However, before reading too much I was prompted with an inescapable form asking for my details in a master data sharing tone.

Well, then I could as well explore the mandatory country list. No surprise. A master (or reference) data havoc. Two Bosnia (and) Herzegovina entries. Two Brunei entries. Two Brazil entries. Two Burma / Myanmar entries.

Country List Havoc by Stibo Systems

RDM: A Small but Important Extension to MDM

Reference Data Management (RDM) is a small but important extension to Master Data Management (MDM). Together with a large extension, being big data and data lakes, mastering reference data is increasingly being part of the offerings from MDM solution vendors as told in the post Extended MDM Platforms.

RDM

Reference Data

Reference data are these smaller lists of values that gives context to master data and ensures that we use the same (or linkable) codes for describing master data entities. Examples are:

Reference data tend to be externally defined and maintained typically by international standardization bodies or industry organizations, but reference data can also be internally defined to meet your specific business model.

3 RDM Solutions from MDM Vendors

Informatica has recently released their first version of a new RDM solution: MDM – Reference 360. This is by the way the first true Software as a Service (SaaS) solution from Informatica in the MDM space. This solution emphasizes on building a hierarchy of reference data lists, the ability to make crosswalks between the lists, workflow (approval) around updates and audit trails.

Reltio has embraced RDM has an integral part of their Reltio Cloud solution where the “RDM capabilities improves data governance and operational excellence with an easy to use application that creates, manages and provisions reference data for better reporting and analytics.

Semarchy has a solution called Semarchy xDM. The x indicates that this solution encompasses all kinds of enterprise grade data and thus both Master data and Reference data while “xDM extends the agile development concept to its implementation paradigm”.