Integration is vital to practically all organizations. There is an increasing demand to make the data available and a constant need to access the data. Digitalization and automation require applications to interact. However, integration errors may lead to an excessively complex and expensive landscape, hindering an organization’s delivery agility. …

“Squid game” became one of the biggest streaming hits in 2021 that took the world by storm. There could be many reasons for its success, but in my opinion, one key reason is that many people were able to connect with it one way or the other. …

The idea of “divide and conquer”​ and “product thinking”​ can lead to effective data management. Product thinking in data i.e. “data as a product” is a mindset and also does not necessarily need a full-blown data mesh — Data as an asset Data as an asset thinking has been around for a while. This thinking is intended to facilitate effective data management, utilization, and likely monetization of data. It provides a baseline for data governance. …

Understanding the implication of performing transformations during data ingestion and of extracting the data that are not yet ready or meant for external consumption — ETL, or Extract Transform Load, has become synonymous with the process of data integration, particularly in data warehouses. ETL has been quite successful, with so many tools focusing on just that. But product/tooling companies sell their products and that is not necessarily always a better architectural choice. …