Jan Bosch
This week, I had an interesting discussion about data with the CEO of one of the startups I work with. The challenge is that many companies are collecting vast amounts of data, storing it and then leaving it as an unused asset. It surprises me that so many companies are maintaining such amazingly large data … Read more
DevOps, DataOps, MLOps – the number of different “Ops” combinations seems to have exploded over the last year or so. There are manifestos, meetups, lots of blog posts and research articles about these various approaches. In order to get clear on terminology, I think it’s good to define what we’re talking about. So, first, DevOps … Read more
In my last column, I presented our research agenda for AI engineering. This time, we’re going to focus on one of the topics on that agenda, ie data versioning and dependency management. Even though the big data era has been with us for over a decade now, many of the companies that we work with … Read more
This week, for the umpteenth time, I met a team in the process of putting a new product in the market, telling me that they were so customer centric. What they meant was that during development, they’d talked to a number of potential customers and some of the employees had used prototypes. For those that … Read more
In recent columns, I’ve been sharing my view on the quality of the data that many companies have in their data warehouses, lakes or swamps. In my experience, most of the data that companies have stored so carefully is useless and will never generate any value for the company. The data that actually is potentially … Read more
During the big data era, one of the key tenets of successfully realizing your big data strategy was to create a central data warehouse or data lake where all data was stored. The data analysts could then run their analyses to their hearts’ content and find relevant correlations, outliers, predictive patterns and the like. In … Read more
Virtually all organizations I work with have terabytes or even petabytes of data stored in different databases and file systems. However, there’s a very interesting pattern I’ve started to recognize during recent months. On the one hand, the data that gets generated is almost always intended for human interpretation. Consequently, there are lots of alphanumeric … Read more
The effects of digitalization and other technological shifts cause companies to realize they need to change. This often leads to significant discussions in the organization as there typically are several alternatives being considered by different people. These might include topics such as business models, product implications, partnerships with suppliers and technology providers. Agreeing on the … Read more
Before digitalization became a thing, the industry was divided into two types of businesses: those that sell products and those that provide services. Those that sell products have a transactional relationship with their customers, mostly consisting of selling one of their products. The service businesses tend to have a more continuous relationship with their customers … Read more
Last week, I wrote about the different types of use for data that we have available. That led to discussions with various people and I realized that there’s a problem around data that’s very typical in companies that have their roots in embedded systems or mechanical engineering: it’s actually unclear who owns the data from … Read more
