Encompassing Relational, Document and Graph the Best Way

The use of graph technology in Master Data Management (MDM) has been a recurring topic on this blog as the question about how graph approaches fits with MDM keeps being discussed in the MDM world.

Multi-Domain MDM GraphRecently Salah Kamel, the CEO at the agile MDM solution provider Semarchy, wrote a blog post called Does MDM Need Graph?

In here Salah states: “A meaningful graph query language and visualization of graph relationships is an emerging requirement and best practice for empowering business users with MDM; however, this does not require the massive redesign, development, and integration effort associated with moving to a graph database for MDM functionality”.

In his blog post Salah discusses how relationships in the multi-domain MDM world can be handled by graph approaches not necessarily needing a graph database.

At Product Data Lake, which is a business ecosystem wide product information sharing service that works very well besides Semarchy MDM inhouse solutions, we are on the same page.

Currently we are evaluating how graph approaches are best delivered on top of our document database technology (using MongoDB). The current use cases in scope are exploiting related products in business ecosystems and how to find a given product with certain capabilities in a business ecosystem as examined in the post Three Ways of Finding a Product.

Room for Improvement in the PIM World

Ventana Stibo ReportThe analyst firm Ventana Research recently made a report called The Next Generation of Product Information Management with the subtitle Maximizing the Potential Value of Products for Customers and Suppliers.

One, perhaps shocking, number mentioned in the report is that there is “room for improvement, as only 5 percent of organizations share all their product data electronically with supply chain partners”.

However, this resonates very well with my experience, as it has been hard to find a good way to share all kind of product information electronically with all your trading partners, as:

  • The most common used way today is exchanging spreadsheets, which is cumbersome and error prone and therefore many companies experience that it simply is not done or only done partly and certainly not timely.
  • Using consensus data pools (eg GS1 GDSN) only covers a fraction of product groups and product data elements with varying penetration and coverage in different geographies
  • Providing supplier product data portals (and customer product data portals) is a flawed one-sided concept as discussed in the post PIM Supplier Portals: Are They Good or Bad?

This is the reason why Product Data Lake has been launched.

You can get an 18 pager write up of the research report free from Stibo Systems here.

PS: If you are a PIM solution vendor or a PIM system integrator you can, as a legal entity, help with and gain from filling this room by becoming a Product Data Lake Commissioner.

MDM Summit Europe 2017 Preview

Next week we have the Master Data Management (and Data Governance) Summit Europe 2017 in London. I am looking forward to be there.

MDMDG2017The Sponsors

Some of the sponsors I am excited to catch up with are:

  • Semarchy, as they have just released their next version multi-domain (now promoted as multi-vector) MDM (now promoted as xDM) offering emphasizing on agility, smartness, intelligence and being measurable.
  • Uniserv, as they specialize in hosted customer MDM on emerging technology infused with their proven data quality capabilities and at the same time are open to coexistence with other multi-domain MDM services.
  • Experian Data Quality, as they seem to be a new entry into the MDM world coming from very strong support for party and location data quality, however with a good foundation for supporting the whole multi-domain MDM space.

The Speakers

This year there are a handful of Danish speakers. Can’t wait to listen to:

  • Michael Bendixen of Grundfos pumping up the scene with his Data Governance Keynote on Key Factors in Successful Data Governance
  • Charlotte Gerlach Sylvest of Coloplast on taking care of Implementing Master Data Governance in Large Complex Organisations
  • Birgitte Yde and Louise Pagh Covenas of ATP telling how they watch after my pension money while being on a Journey Towards a New MDM System
  • Erika Bendixen of Bestseller getting us dressed up for Making Master Data Fashionable by Transforming Information Chaos into a Governance-Driven Culture.

10 Analyst Firms in the MDM Space

When working with Master Data Management (MDM) it is always valuable to follow the analyst firms that are active on this subject and the related subjects as data quality, data governance and data management in general. You can learn from their insights – and disagreements – on the matters. Here are 10 analyst firms I follow:

Gartner, the large analyst firm known for their magic quadrants, hype cycles and cool vendor lists. There is a lot of brain power in this firm and they have never been caught in admitting a mistake. Quite a lot of posts on this blog mentions Gartner.

Forrester, another firm with heaps of analysts. Forrester has though been less prominent in the MDM world since Robert Karel left for Informatica. However, there are lots of wider insights to gain from as mentioned in the post Ecosystems are The Future of Digital and MDM.

The MDM Institute, which basically is Aaron Zornes, known as the Father Christmas of MDM. Aaron Zornes was the inspirational source in my recent post called MDM as Managed Service.

The Information Difference, headed by Andy Hayler. They publish a yearly MDM landscape report latest referenced on this blog in the post Emerging Database Technologies for Master Data.

Bloor Group has occasionally made reports about MDM latest mentioned on this blog in the post The MDM Market Wordle.

Ventana Research has been especially active around Product Information Management (PIM) as seen in the recent press release on their Product Information Management Research.

Intelligent Business Strategies, run by Mike Ferguson. No nonsense, plain English insights from the around the UK Midlands. Home page here.

Constellation Research, the Silicon Valley perspective. Home page here.

The Group of Analysts has published a series of interviews with MDM and PIM notabilities as for example this one with Richard Hunt of Agility Multichannel on Content Gravity.

Aberdeen Group, a company you as a MDM vendor can hire to put numbers on your blog as for example Stibo Systems did here.

Analysts

MDM as Managed Service

This month I am going to London to attend the Master Data Management Summit Europe 2017.

As a teaser before the conference Aaron Zornes made a post called MDM Market 2017-18: Facts vs. Beliefs (with apologies to current political affairs fans!).

In his article, Aaron Zornes looks at the slow intake of multi-domain MDM, proactive data governance, graph technology and Microsoft stuff ending with stating that MDM as MANAGED SERVICE = HOT:

“Just as business users increasingly gave up on IT to deliver modest CRM in a timely, cost effective fashion (remember all the Siebel CRM debacles), so too are marketing and sales teams especially looking to improve the quality of their customer data… and pay for it as a “service” rather than as a complex, long-time-to-value capital expenditure that IT manages”.

Master Data ShareI second that, having been working with the iDQ™ service years ago, and will add, that the same will be true for product data as well and then eventually also multi-domain MDM.

How that is going to look like is explained here on Master Data Share.

Data Quality for the Product Domain vs the Party Domain

Same Same But Different

The difference between solving data quality issues for party (customer, supplier and other business partner) master data and product master data was discussed 7 years ago on this blog in the post Same Same But Different.

Data Quality Dimensions
Some data quality dimensions

Since then I have worked intensively with both party master data and product master data and the data quality challenges organizations have within these domains.

Building on the findings from 7 years ago and recent experiences, I think there are two areas it is worth emphasizing on:

  • Data Quality Dimensions: All dimensions are important and they support each other in solving the issues. But there are some differences as explained in the post Multi-Domain MDM and Data Quality Dimensions. In my mind, uniqueness is the worst pain for party master data and completeness is the worst pain for product master data.
  • External Data Sources: The use of data sources was examined in the post 1st Party, 2nd Party and 3rd Party Master Data. In my mind, extensive utilization of third party data is paramount for party master data quality and effective exchange of second party data is paramount for product master data quality.

A Sharing Concept

For solving both party master data and product master data quality issues you need Multi-Domain MDM for business ecosystems as proposed in the Master Data Share concept.

Ecosystems are The Future of Digital and MDM

A recent blog post by Dan Bieler of Forrester ponders that you should Power Your Digital Ecosystems with Business Platforms.

In his post, Dan Bieler explains that such business platforms support:

·      The infrastructure that connect ecosystem participants. Business platforms help organizations transform from local and linear ways of doing business toward virtual and exponential operations.

·      A single source of truth for ecosystem participants. Business platforms become a single source of truth for ecosystems by providing all ecosystem participants with access to the same data.

·      Business model and process transformation across industries. Platforms support agile reconfiguration of business models and processes through information exchange inside and between ecosystems.

A single source of truth (or trust) for ecosystem participants is something that rings a bell for every Master Data Management (MDM) practitioner. The news is that the single source will not be a single source within a given enterprise, but a single source that encompasses the business ecosystem of trading partners.

Gartner Digital Platforms.png

Gartner, the other analyst firm, has also recently been advocating about digital platforms where the ecosystem type is the top right one. As stated by Gartner: Ecosystems are the future of digital.

I certainly agree. This is why all of you should get involved at Master Data Share.