In his recent article Andrew Ng defines the term Data-Centric AI as the discipline of systematically engineering the data needed to successfully build an AI system. Instead of focusing on the code to improve the model, the focus is on...
Manufacturers in Germany are only slowly adopting the cloud. Of the three current most popular public cloud providers Microsoft, Amazon and Google, the Microsoft Azure cloud seems to be the most popular one.
The prevailing approach to data architecture of the last, say, decade was to centralize your data in one place, namely a data warehouse or (later) a data lake. This means physically copying the data from all the various source systems...
Every time I look back at the middle of a project, without exception, I feel that I started working (coding) too soon. Whether employed or freelance, there’s always a pressure to deliver. Managers or clients want to see results -...
I recently heard a story about “unlinked coils”. These are coils that are produced but that are not assigned to a production order in the ERP. This means the are not assigned to a sales order either. As a result...
One of the biggest challenges I face as a data engineer is the problem of data discoverability. The most common questions I get at work is “where can I find the data for variable X?” and “What do the numbers...
Two barriers that obstruct the implementation of AI in manufacturing are: