ETL vs. ELT
Both describe when the transformation happens: ETL (Extract, Transform, Load) transforms the data before loading it into the target system. ELT first loads the raw data and transforms it within the target system (data warehouse) — flexible when the target system is powerful.
Batch vs. Streaming
Batch processes large volumes at intervals (hourly, daily) — ideal for reporting and history. Streaming processes data as soon as it arrives — for immediate insight and response (e.g. predictive maintenance).
Lambda architecture
Where both are needed, the Lambda architecture combines the two paths: a batch layer for complete, accurate history, a speed layer for low latency, and a serving layer that merges both results.
From the device to the analysis
Because we understand the data source itself (sensor, electronics, embedded), a clean pipeline begins right at acquisition — often at the edge — and extends all the way to the analysis. The paths in between are shown by the IoT architecture.