From test bench to lakehouse: how AVL modernizes measurement data analytics with Impulse

AVL, an automotive testing company, built a lakehouse platform for measurement data analytics using Impulse, an open-source Python library from Databricks Labs. A single automotive test campaign can generate hundreds of terabytes of time-series sensor data in binary formats like ASAM MDF4. Impulse introduces a Time Series Analytics Language (TSAL) that lets domain engineers define channel selections, virtual signals, events, and aggregations in ~10 lines of Python, which are then translated into distributed Spark execution across all recordings. The platform follows Medallion Architecture with Bronze ingestion, a hierarchical Silver layer for validated data, and Gold-layer star schemas for BI and ML. Three usage modes are supported: structured reporting for scheduled pipelines, ad-hoc DataFrame exploration, and ML feature extraction. AVL reports quantitative and qualitative improvements in analysis scalability, reproducibility, and governance compared to traditional desktop tools like MATLAB or NI DIAdem.

Source: https://www.databricks.com/blog/test-bench-lakehouse-how-avl-modernizes-measurement-data-analytics-impulse. 8 Sync News only summarizes and links out; content copyright belongs to the authors and original sources.