From Data Lakehouses to Event-Driven Architecture — Master 12 data concepts and switch them into easy projects to remain ahead in IT.
Once I scroll through YouTube or LinkedIn and see topics like RAG, Agents or Quantum Computing, I sometimes get a queasy feeling about maintaining with these innovations as a knowledge skilled.
But after I reflect then on the topics my customers face day by day as a Salesforce Consultant or as a Data Scientist at university, the challenges often seem more tangible: examples are faster data access, higher data quality or boosting employees’ tech skills. The important thing issues are sometimes less futuristic and may normally be simplified. That’s the main focus of this and the subsequent article:
I even have compiled 12 terms that you’re going to definitely encounter as a knowledge engineer, data scientist and data analyst in 2025. Why are they relevant? What are the challenges? And how are you going to apply them to a small project?
So — Let’s dive in.
Table of Content
1 — Data Warehouse, Data Lake, Data Lakehouse
2 — Cloud platforms as AWS, Azure & Google Cloud Platform
3 — Optimizing data storage
4 — Big data technologies reminiscent of Apache Spark, Kafka
5 — How data integration becomes real-time capable: ETL, ELT and Zero-ETL
6 — Even-Driven Architecture (EDA)
Term 7–12 partly 2: Data Lineage & XAI, Gen AI, Agentic AI, Inference Time Compute, Near…
