Master Data

External Events, MDM and Data Stewardship

Henrik Gabs Liliendahl2 Comments

Exploiting external data is an essential part of party master data management as told in the post Third-Party Data and MDM.

TimingExternal data supports data quality improvement and prevention of party master data by:

  • Ensuring accuracy of party master data entities best at point of entry but sometimes also by later data enrichment
  • Exploring relationships between master data entities and thereby enhance the completeness of party master data
  • Keeping up the timeliness of party master data by absorbing external events in master data repositories

External events around party master data are:

Updating with some of these events may be done automatically and some events requires manual intervention.

Right now I’m working with data stewardship functionality in the instant Data Quality MDM Edition where the relocation event, the deceased event and other important events in party master data life-cycle management is supported as part of a MDM service.

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Winning by Sharing Data

Henrik Gabs Liliendahl1 Comment

When I changed my laptop a few months ago, it was the easiest migration to a new computer ever.

Basically I just had to connect to all the services in the cloud I had been using before and for many services the path was to get connected to Google+, Twitter and FaceBook and then connect to many other services via these connections.

ShareThis was a personal win.

Most of the teams I am working with are sharing their data with me in the cloud. As in the bad old days I do not have to call and ask for progress on this and that. I can check the status myself and even get notifications on my phablet when a colleague completes a task.

ShareThis is a shared win.

Within my profession being data quality improvement and Master Data Management (MDM) sharing data is going to be a winning path too as told in the post Sharing is the Future of MDM.

There are several ways of sharing master data like using commercial third party data, digging into open government data, having your own data locker and relying on social collaboration. These options are examined in the post Ways of Sharing Master Data.

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Omni-purpose MDM

Henrik Gabs Liliendahl4 Comments

The terms omni-channel banking and omni-channel retailing are becoming popular within businesses these days.

In this context omni (meaning all) is considered to be something more advanced than multi (meaning many) as in multi-channel retailing.

Data management, including Master Data Management (MDM), is always a bit behind the newest business trends. In our discipline we have hardly even entered the multi stage yet.

Some moons ago I wrote about multi-channel data matching on the Informatica Perspectives blog in the post Five Future Data Matching Trends. Today, on the same blog, Stephan Zoder has the post asking: Is your social media investment hampered by your “data poverty”?

Herein Stephan examines the possible benefits of multi-channel data matching based on a business case within the gambling industry.

Using omni in relation to MDM was seen in a vendor presentation at the Gartner MDM Summit in London last week as reported in the post Slicing the MDM Space. Omnidomain MDM was the proposed term here.

The end goal should probably be something that could be coined as omni-purpose MDM. This will be about advancing MDM capabilities to cover multiple domains and embrace multiple channels in order to obtain a single view of every core entity that can be used in every business process.

Omni

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The Intersections of Big Data, Data Quality and Master Data Management

Henrik Gabs Liliendahl3 Comments

This blog has since 2009 been very much about the intersection between Master Data Management (MDM) and data quality. These two disciplines are closely related as the vast majority of work with data quality improvement going on is related to master data taking some slightly different forms depending on if we are fighting with party master data, product master data, location master data or other master data domains.

Big Data Quality MDMIn mid 2011 the term big data became more popular than data quality as reported in post Data Quality vs Big Data. After initial euphoria about big data and focus on the analytical side of big data the question about big data quality has fortunately gained traction. Apart from the quality of the algorithms used in big data analytics the quality of the big data is definitely a factor to be taken very serious when deciding to act on the outcomes of big data analytics.

There are questions about the quality of the big data itself as for example told in the post Crap, Damned Crap, and Big Data. This story is about social data and how crappy these data streams may be. Another prominent flavor of big data is sensor data where there also may be issues of data quality as in the example mentioned in the post Going in the Wrong Direction.

As examined in the latter example the quality of big data will in many cases have to be measured by how well big data relates to internal master data and external reference data. You may find more examples of that in the post Big Data and Multi-Domain Master Data Management.

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Slicing the MDM Space

Henrik Gabs Liliendahl4 Comments

Master DataThese days I am attending the Gartner MDM summit in London.

MDM (Master Data Management) initiatives and MDM solutions are not created equal and different ways of slicing the MDM world were put forward on the first day.

Gartner is famous for the magic quadrants and during the customer master data quadrant presentation I heard Bill O’Kane explain why this is a separate quadrant from the product master data quadrant and why there are no challengers and no visionaries.

In another session about MDM milestones Bill O’Kane for this context sliced the MDM world a bit differently based on moving between MDM styles. Here we had:

  • Business-to-consumer (B2C) Customer Data Integration (CDI)
  • Business-to-business (B2B) customer MDM, Product Information Management (PIM) and other domains.

The vendors in general seems to want to do everything MDM.

Stibo Systems, a traditional PIM vendor, presented the case for multidomain MDM based on how things have developed within eCommerce. Stibo even smuggled the term omnidomain MDM into the slides. A marketing gig in the making perhaps.

The megavendors has bought who ever they need to be multidomain.

Some new solutions are born in the multidomain age. Semarchy is an interesting example as they are so the evolutionary way.

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Data Entry by Employees

Henrik Gabs Liliendahl4 Comments

A recent infographic prepared by Trillium Software highlights a fact about data quality I personally have been preaching about a lot:

Trillium 75 percent

This number is (roughly) sourced from a study by Wayne W. Eckerson of The Data Warehouse Institute made in 2002:

TDWI 76 percent

So, in the fight against bad data quality, a good place to start will be helping data entry personnel doing it right the first time.

One way of achieving that is to cut down on the data being entered. This may be done by picking the data from sources already available out there instead of retyping things and making those annoying flaws.

If we look at the two most prominent master data domains, some ideas will be:

  • In the product domain I have seen my share of product descriptions and specifications being reentered when flowing down in the supply chain of manufacturers, distributors, re-sellers, retailers and end users. Better batch interfaces with data quality controls is one way of coping with that. Social collaboration is another one as told in the post Social PIM.
  • In the customer, or rather party, domain we have seen an uptake of using address validation. That is good. However, it is not good enough as discussed in the post Beyond Address Validation.

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Attending a MDM Summit

Henrik Gabs Liliendahl3 Comments

Going to MDM (Master Data Management) conferences is a great learning experience.

If we look at world-wide conferences there are two series of conferences going on every year:

  • The Master Data Management Summit series lead by the MDM Institute, which is Aaron Zornes
  • The Master Data Management summit series organized by Gartner (the analyst firm)

Both those traveling events are coming to London this spring. First up is the Gartner event the 12th and 13th March. As I have been to the Zornes show several times before, I am looking forward to be at the more expensive Gartner performance this year.

The learning actually starts when you are looking at company names on the attendee list. Some master data issues are showcased here:

There will be people from these three well-known British supermarkets:

GartnerMDM 1

The good folks at Kühne + Nagel (AG & Co.) KG is having a hard time putting their proper name in there:

GartnerMDM 2

And what a timely name for this Swiss company:

GartnerMDM 3

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Agile MDM. Using IT.

Henrik Gabs Liliendahl1 Comment

MDM (Master Data Management) projects may have a bad name as large IT projects using huge amount of resources, taken a lot of time and ending up with producing very little measurable results.

This phenomenon isn’t new at all in the IT world. There are often two answers to that challenge:

  1. Don’t treat it as an IT project. It’s all about people and culture.
  2. Do it the agile way using IT.

Lean Evolutionary MDMAfter having a lot of fun with option one you will sooner or later realize that the master data pain points still exists and then come to option two.

I have earlier written some agile posts about Lean MDM and Eating the MDM Elephant and the relevance of having MDM technology that supports the agile way has in my eyes only become more and more apparent since then.

What are your experiences? Who is doing agile MDM – using IT? Is it good?

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Multi-Domain MDM Uptake

Henrik Gabs Liliendahl3 Comments

Within Master Data Management (MDM) doing multi-domain MDM has been trending for a couple of years. Yesterday Gartner (the analyst firm) had a chat session on twitter preceding the upcoming Gartner MDM summits around the world.

Along the way @BillOKane of @Gartner_inc revealed some numbers about multi-domain MDM from the Gartner camp:

Multi-Domain 1

Multi-Domain 2

So, stating these numbers using the MoSCoW method we have that among companies considering MDM:

  • 3 % sees multi-domain MDM as a MUST have now
  • 10 % thinks they SHOULD have multiple-domain MDM now
  • 17 % regards multi-domain MDM as something they COULD have now
  • 70 % WONT have multi-domain MDM now

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Sharing Big Location Reference Data

Henrik Gabs Liliendahl2 Comments

In the post Location Data Quality for MDM the different ways of handling location master data within many companies was examined.

A typical “as is” picture could be this:

Location1

Location data are handled for different purposes using different kinds of systems. Customer data may be data quality checked by using address validation tools and services, which also serves as prerequisite for better utilization of these data in a Geographical Information System (GIS) and in using internal customer master data in marketing research for example by utilizing demographic classifications for current and prospective customers.

Often additional external location data are used for enrichment and for supplementing internal master data downstream in these specialized systems. It may very well be that the external location reference data used at different points does not agree in terms of precision, timeliness, conformity and other data quality dimensions.

A desired “to be” picture could be this:

Location2

In this set-up everything that can be shared across different purposes are kept as common (big) reference data and/or are accessible within a data-as-a-service environment maintained by third party data providers.

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