BIO
BIO
These are a few key periods that have taught me how to deal with an abundance of distributed and fragmented data. At least, this is the data landscape that is revealing itself to us and that we want to deal with smartly.
1990
THE INFORMATION EXPLOSION
- In the last 2 decades of the last century, with the emergence of electronic media such as the CD-ROM, the Internet, access to more and more data and information came quite rapidly. Great of course for all the new possibilities and the new opportunities it offered.
- I just started working for Philips, among others, with a focus on CD-ROM, working with the big publishers, but also the car industry and many others who appeared to have huge amounts of information and saw opportunities
2000
THE INFORMATION OVERLOAD
- Pretty soon after huge amounts of information became available, came the challenges of finding and then working with it. Search engines began to take hold.
- I implemented many enterprise search engines for various organisations (government, multi-nationals and specialists) and learned a lot about distributed data sources, data contracts and governance.
2005
BIG DATA AVANT LA LETTRE
- The term Big Data came into vogue from 2005, referring to large amounts of data, in huge variety and at high speed that needed to be made available and usable for advanced analytics.
- I have always regarded documents as containers for data: data partly in tabular form, images, and text. In text, you can discover a lot of data with techniques that were very advanced at the time, such as entity extraction, sentiment analysis, triples and knowledge graphs. Back then, I did a lot myself; now the tools have become cloud services.
2010
DATA ARCHITECTURE
- Data started flowing more and more, networks became more robust and faster, data processing went faster and faster. The question became increasingly topical: how do we make data flow?
- With a passion for machines (real machines, as you learn in mechanical engineering studies), this was a logical step for me. I designed multiple architectures to pull data from all kinds of sources (databases, websites, data services, etc.), handle and store large volumes, robust environments that could take a beating.
1995
DOCUMENT MANAGEMENT, KNOWLEDGE MANAGEMENT AND DATA MANAGEMENT
- All technologies together are only as good as the people and processes that use them. I discovered this during my first document management project. You can do very nice things, but people have to see the point, it has to give them something and there is always a big or small change process attached to it.
- Afterwards, I also did knowledge management projects and there, too, it is clear: people have to want it, you have to seduce them, you have to teach them and occasionally use pressure to make sure you achieve your goals. Often, you also don’t have people under your direct control and so you ‘borrow’ capacity. Not the easiest way of moving forward, you have to earn it.
2021
ACCELERATING DATA MANAGEMENT
- Having worked as a consultant for many years, I noticed that while I was constantly doing new and different roles in data management, I also noticed that at the conclusion of my project, there was often a big setback because the in-house organisation had not been able to build sufficient knowledge. I also noticed that I regularly got movement in one part of the organisation, but that the rest of the organisation could not take over.
- I then made the decision that I can support organisations better if I teach them to do it themselves. Besides doing, that includes continuing to learn and also putting a focus on communication between departments, between business units and the different layers in the organisation. In my experience, the best way to become more data mature as an organisation.I also became President of DAMA Netherlands in that year. In this position, I encourage and help professionals to work together to deepen and update our knowledge of all aspects of managing data.
1990
THE INFORMATION EXPLOSION
- In the last 2 decades of the last century, with the emergence of electronic media such as the CD-ROM, the Internet, access to more and more data and information came quite rapidly. Great of course for all the new possibilities and the new opportunities it offered.
I just started working for Philips, among others, with a focus on CD-ROM, working with the big publishers, but also the car industry and many others who appeared to have huge amounts of information and saw opportunities.
2000
THE INFORMATION OVERLOAD
- Pretty soon after huge amounts of information became available, came the challenges of finding and then working with it. Search engines began to take hold.
I implemented many enterprise search engines for various organisations (government, multi-nationals and specialists) and learned a lot about distributed data sources, data contracts and governance.
2005
BIG DATA AVANT LA LETTRE
- The term Big Data came into vogue from 2005, referring to large amounts of data, in huge variety and at high speed that needed to be made available and usable for advanced analytics.
I have always regarded documents as containers for data: data partly in tabular form, images, and text. In text, you can discover a lot of data with techniques that were very advanced at the time, such as entity extraction, sentiment analysis, triples and knowledge graphs. Back then, I did a lot myself; now the tools have become cloud services.
2010
DATA ARCHITECTURE
- Data started flowing more and more, networks became more robust and faster, data processing went faster and faster. The question became increasingly topical: how do we make data flow?
With a passion for machines (real machines, as you learn in mechanical engineering studies), this was a logical step for me. I designed multiple architectures to pull data from all kinds of sources (databases, websites, data services, etc.), handle and store large volumes, robust environments that could take a beating.
1995
DOCUMENT MANAGEMENT, KNOWLEDGE MANAGEMENT AND DATA MANAGEMENT
- All technologies together are only as good as the people and processes that use them. I discovered this during my first document management project. You can do very nice things, but people have to see the point, it has to give them something and there is always a big or small change process attached to it.
Afterwards, I also did knowledge management projects and there, too, it is clear: people have to want it, you have to seduce them, you have to teach them and occasionally use pressure to make sure you achieve your goals. Often, you also don’t have people under your direct control and so you ‘borrow’ capacity. Not the easiest way of moving forward, you have to earn it.
2021
ACCELERATING DATA MANAGEMENT
- Having worked as a consultant for many years, I noticed that while I was constantly doing new and different roles in data management, I also noticed that at the conclusion of my project, there was often a big setback because the in-house organisation had not been able to build sufficient knowledge. I also noticed that I regularly got movement in one part of the organisation, but that the rest of the organisation could not take over.
I then made the decision that I can support organisations better if I teach them to do it themselves. Besides doing, that includes continuing to learn and also putting a focus on communication between departments, between business units and the different layers in the organisation. In my experience, the best way to become more data mature as an organisation.
I also became President of DAMA Netherlands in that year. In this position, I encourage and help professionals to work together to deepen and update our knowledge of all aspects of managing data.