A recent infographic prepared by Trillium Software highlights a fact about data quality I personally have been preaching about a lot:
This number is (roughly) sourced from a study by Wayne W. Eckerson of The Data Warehouse Institute made in 2002:
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.
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:
The good folks at Kühne + Nagel (AG & Co.) KG is having a hard time putting their proper name in there:
And what a timely name for this Swiss company:
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:
- Don’t treat it as an IT project. It’s all about people and culture.
- Do it the agile way using IT.
After 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?
”Data is the new oil” is a well-known term today used to emphasize on the fact that data and your ability to exploit data can make you rich.
The rise of big data has put some more fire to this burning issue indeed with the variant saying “Big data is the new oil”.
Now, as oil is many things, data is many things too. As few of us actually use crude oil, also called petroleum, few of us don’t use raw data to get rich. We use information distilled from raw data for specific purposes. One example is examined in the post Mashing Up Big Reference Data and Internal Master Data.
This brings me to that we have the question of quality of oil just as we have the question of the quality of data as explained nicely by Ken O’Connor in the post Data is the new oil – what grade is yours?
Yesterday I participated in an information meeting at the Danish Ministry for Business and Growth related to an initiative around using open government data within business intelligence in the private sector.
Using open government data is already an essential part of the instant Data Quality concept I’m working with right now and I have earlier written about the state of open government data in Denmark in the posts Government Says So and Making Data Quality Gangnam Style.
At the meeting some well-known questions came up:
Is this big data?
The answer was, that it isn’t exactly big data mainly because the data are well structured and thereby looks more as the traditional data sources that we have been used to working with for many years.
Personally I, if we have to use the big word, like to see these data as big reference data as told in the post Four Flavors of Big Reference Data.
What about data quality?
The answer here was a hope about that the fact that these data was made open for the private sector will create some data quality feedback resulting in that the public sector would improve quality of the data to the benefit of both public sector and private sector data consumers.
Many moons ago I wondered how my social influence is measured as told in the post Klout Data Quality.
Since then my Klout has dropped a bit from 59 to 57. It does not ruin my day, but I wonder why. A thing that strikes me is from where I get my Klout. It seems Twitter is the place as it counts for 73 % of my Klout. LinkedIn is only 8 %. Personally, I would give them opposite importance.
Recently I noticed I was included in a list called Top 200 Thought Leaders in Bigdata Analytics. Honorable maybe. However, I am afraid it merely is a count of how many #Bigdata tags I have used on Twitter relative to others.
What matters to me in social influence seems to be out of scope for Klout, as it is readers and comments on this blog.
What about you. Do you have the right Klout? Is it measured the right way?
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:
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