all topics
· Topic
Data Engineering
Spark, Kafka, lakehouses and petabyte pipelines. Build data that engineers can trust.
Roadmap
stage 1
Foundations
stage 2
Core patterns
stage 3
Advanced
stage 4
In production
Articles
- beginner 5m
Kafka 101 for ML engineers
Topics, partitions, consumer groups — the parts of Kafka that actually matter when you put ML features behind it.
- advanced 16m
Taking the Azure Fabric Ignite Edition Challenges to Complete
Microsoft Learn Challenge conducting a challenge to get good in few of the challenges which are super useful to complete to gain knowledge on Microsoft Fabric.
- intermediate 15m
Exploring different services in GCP
Exploration and documentation of different services offered in GCP
- intermediate 11m
Exploring Azure Data Explorer and Best Practices
A self-sufficient deep-dive on Azure Data Explorer (ADX/Kusto) — architecture, the KQL language from zero to advanced, ingestion patterns, performance/cost levers, and operational best practices.