Recently the Global Agenda Council on Emerging Technologies within the World Economic Forum has made a list of the top 10 emerging technologies for 2012. According to this list the technology with the greatest potential to provide solutions to global challenges is informatics for adding value to information.
As said in the summary: “The quantity of information now available to individuals and organizations is unprecedented in human history, and the rate of information generation continues to grow exponentially. Yet, the sheer volume of information is in danger of creating more noise than value, and as a result limiting its effective use. Innovations in how information is organized, mined and processed hold the key to filtering out the noise and using the growing wealth of global information to address emerging challenges.”
Big data all over
Surely “big data” is the buzzword within data management these days and looking for extreme data quality will be paramount.
Filtering out the noise and using the growing wealth of global information will help a lot in our endurance to make a better world and to make better business.
In my focus area, being master data management, we also have to filtering out the noise and exploit the growing wealth of information related to what we may call Big Master Data.
Big external reference data
The growth of master data collections is also seen in collections of external reference data.
For example the Dun & Bradstreet Worldbase holding business entities from around the world has lately grown quickly from 100 million entities to over 200 millions entities. Most of the growth has been due to better coverage outside North America and Western Europe, with the BRIC countries coming in fast. A smaller world resulting in bigger data.
Also one of the BRICS, India, is on the way with a huge project for uniquely identifying and holding information about every citizen – that’s over a billion. The project is called Aadhaar.
When we extend such external registries also to social networking services by doing Social MDM, we are dealing with very fast growing number of profiles in Facebook, LinkedIn and other services.
Surely we need informatics for adding the value of big external reference data into our daily master data collections.
Liliendahl on Data Quality 
Informatics presents as many threats as it does opportunities. The filtering that goes on with informatics, for example, Google’s delivering what you are ‘interested in’ based on what you have previously searched is now delivering us all with a completely distorted view of the world based on our habits and preconceptions.
We will now all have our prejudices and distortions confirmed, as Google delivers ‘information’ that leads us to believe that this is what the rest of the world believes – that what we are reading is fact!
Big Data = Big Mess. Current MDM practices (which have regressed 25 years) are already starting in the wrong place and heading in the wrong direction. Adding more data will simply magnify the mess. If MDM practitioners cannot build the equivalent of a “mud hut” what makes them believe that they can build a “skyscraper”.
All of the data coming our way does present opportunities. However, those trying to exploit it need to get themselves up to speed with the fundamentals of quality data modelling techniques or the world will, paradoxically, end up far more ill informed than it has ever been!!!
John, true, we need to get up to speed with quality data modelling techniques.
However, there are two ways in which data may be of high quality:
• If they are fit for the purpose of use
• If they correctly reflect the real world
Neither of these benchmarks is optimal and they are often conflicting.
MDM has historically focused on the first benchmark. The increased availability of external reference data will bend in direction of the latter benchmark. Perhaps we will get a better mix.
But surely, we will not get there without getting up to speed with some fundamentals.