At this time of the year, it is custom to make a foreseeing about what will happen next year usually within a specific area – as for example data management.
After 2020 one should think that making any qualified guess about next year should be regarded within a huge amount of uncertainty.
Well, let us have a go anyway.
The horrible year of the outbreak of the pandemic has also affected the data management scene. One often mentioned theme is the accelerated digitalization, which all the bad things about the pandemic aside, seen in isolation (so to speak), is a positive development.
Digitalization also push globalization. Now you do not have to work with data management partners who is within a 5 miles reach – 5,000 kilometres will be the same.
In fact, the outlook for the data management industry is not bad at all. Digital transformation initiatives will require investments in data management consultancy, data management services and data management technology. The competition will intensify with many partners available at a global range. This will be an opportunity for smaller consultancies with broad visions, nimble service providers with scalable offerings and forward-looking tool vendors with doable solutions.
The chances for gaining market shares in a developing market are good for those of you who sell data management stuff.
The chances for getting the best help are good for those of you who buy data management stuff.
A Merry Christmas to you who celebrate this and a Happy Calendar New Year to all of you.
There are several parameters considered by organizations on the look for solutions that handles Master Data Management (MDM) and Product Information Management (PIM) or both. One is how MDM’ish or PIM’ish the solution is as examined in the post MDM, PIM or Both.
Another aspect is the geographical presence. This includes where the solution provider is based and of course also the presence around the world through local offices and partner network.
Here are some of the solution providers from North America and Europe on a map:
We also see statistics showing a development towards melting ice masses with rising sea levels as the foreseeable result. However, statistics can always be questioned. Is the ice thickening somewhere else? Has this happened many times before?
These kind of questions shows the layers we must go through getting from data quality to information quality, then decision quality and on top the wisdom in applying the right knowledge whether that is to achieve business outcomes or avoiding climate change.
The latest market report on data quality tools from Information Difference is out. In the introduction to the data quality landscape Q1 2019 this example of the consequences of a data quality issue is mentioned: “Christopher Columbus accidentally landed in America when he based his route on calculations using the shorter 4,856 foot Roman mile rather than the 7,091 foot Arabic mile of the Persian geographer that he was relying on.”.
Information Difference has the vendors on the market plotted this way:
As reported in the post Data Quality Tools are Vital for Digital Transformation also Gartner recently published a market report with vendor positions. The two reports are, in terms on evaluating vendors, like Roman and Arabic miles. Same same but different and may bring you to a different place depending on which one you choose to use.
Vendors evaluated by Information Difference but not Gartner are veteran solution providers Melissa and Datactics. On the other side Gartner has evaluated for example Talend, Information Builders and Ataccama. Gartner has a more spread out evaluation than Information Difference, where most vendors are equal.
PS: If you need any help in your journey across the data quality world, here are some Popular Offerings.
The way governments around the world has organized their Master Data Management (MDM) is quite different. When it comes to registering citizens, the practice varies a lot as described in the post Citizen Master Data Management.
I have lived most of my years in Denmark where our national ID is unique and used for everything by public agencies and also a lot by private companies. Some years ago I lived in the United Kingdom, where the public agencies (and my bank) had no clue about who I were, when I came, what I did and when I left.
Recently the World Economic Forum has circulated some videos on LinkedIn telling about how stuff is done differently around the world. The video below is about the Danish civil registry (which by the way is similar in other Scandinavian countries):
What do you think? Would this public MDM and data quality practice work in USA, UK, Germany or where else you live?
During my engagements in selecting and working with the major data management tools on the market, I have from time to time experienced that they often lack support for specialized data management needs in minor markets.
Two such areas I have been involved with as a Denmark based consultant are:
The authorities in Denmark offers a free of charge access to very up to data and granular accurate address data that besides the envelope form of an address also comes with a data management friendly key (usually referred to as KVHX) on the unit level for each residential and business address within the country. Besides the existence of the address you also have access to what activity that takes place on the address as for example if it is a single-family house, a nursing home, a campus and other useful information for verification, matching and other data management activities.
If you want to verify addresses with the major international data managements tools I have come around, much of these goodies are gone, as for example:
Address reference data are refreshed only once per quarter
The key and the access to more information is not available
A price tag for data has been introduced
In Denmark (and other Scandinavian countries) we have a national identification number (known as personnummer) used much more intensively than the national IDs known from most other countries as told in the post Citizen ID within seconds.
The data masking capabilities in major data management solutions comes with pre-build functions for national IDs – but only covering major markets as the United States Social Security Number, the United Kingdom NINO and the kind of national id in use in a few other large western countries.
So, GDPR compliance is just a little bit harder here even when using a major tool.
When you buy stuff one of the characteristics you may emphasis on is where the stuff is made: The country of origin.
Buying domestic goods has always been both a political issue and something that in people’s mind may be an extra quality sign. When I lived in The UK I noticed that meat was promoted as British (maybe except from Danish bacon). Now when back in Denmark all meat seems to be best when made in Denmark (maybe except from an Argentinian beef). However, regulations have already affected the made in marking for meat, so you have to state several countries of origins in the product lifecycle.
Country of origin is a product data element that you need to handle for regulatory reasons not at least when moving goods across borders. Here it is connected with commodity codes telling what kind of product it is in the custom way of classifying products as examined in the post Five Product Classification Standards.
When working with product data management for products that moves cross border you are increasingly asked to be more specific about the country of origin. For example, if you have a product consisting of several parts, you must specify the country of origin for each part.
This blog is in English. However, as a citizen in a country where English is not the first language, I have a problem with English. Which flavour or flavor of English should I use? US English? British English? Or any of the many other kinds of English?
It is, in that context, more a theoretical question than a practical one. Despite what Grammar Nazis might think, I guess everyone understands the meaning in my blend of English variants and occasional other spelling mistakes.
The variants of English, spiced up with other cultural and administrative differences, does however create real data quality issues as told in the post Cultured Freshwater Pearls of Wisdom.
When working with Product Data Lake, a service for sharing product information between trading partners, we also need to embrace languages. In doing that we cannot just pick English. We must make it possible to pick any combination of English and country where English is (one of) the official language(s). The same goes for Spanish, German, French, Portuguese, Russian and many other languages in the extend that products can be named and described with different spelling (in a given alphabet or script type).
You always must choose between standardization or standardisation.
Facebook is set to fight fake news by using artificial intelligence. A good way to practice may be by playing a bit more around with their geolocation intelligence.
Today I, as far as I know, are on the Canary Islands. This is a part of Spain, though a little bit away from the motherland down the Atlantic Ocean off the North African coast. A main town on the islands is called Las Palmas.
However, according to Facebook I seem to be in a place called Las Palmas Subdivision on Hawaii in the Pacific Ocean on the other side of the globe with Hawaii being a bit away from where it were last time I looked on a map.