Data Model

Start with three tables

DefaultSolver needs only three tables: container_metrics, channel_metrics, and channels. The tag tables (container_tags, channel_tags) and the channel_mapping / unit_conversion tables are fully optional add-ons, used only when configured — see the Query Engine table requirements.

The rest of this page documents the full shape. Landing your data in it during ingest is the simplest path (see the Ingestion guide); if you can't reshape, a SolverConfig can remap column names, or you can implement a custom solver.

Impulse operates on Databricks Medallion Architecture.

Raw measurement files are ingested into the lakehouse in the bronze layer. These are then processed and transformed into a normalized Silver layer. Gold Layer contains the final analytics results in a star schema optimized for querying and reporting.

All layers are stored as Delta tables in Unity Catalog, which makes them easy to govern, secure, and queryable by various personas across the organization.

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Silver Layer (Input)

Only three tables are required — container_metrics, channel_metrics, and channels. The two tag tables (container_tags, channel_tags) are fully optional: add them only when you want tag-based container filtering or EAV channel selection.

Table	Required?	Purpose
container_metrics	Yes	One row per measurement container with timestamps, duration, and channel count.
channel_metrics	Yes	Pre-computed statistics per channel (min, max, mean, percentiles, sample count). Also carries channel-selection columns (e.g. channel_name) in the wide model.
channels	Yes	Time-series sample data, either as raw (timestamp, value) samples or as run-length-encoded intervals [tstart, tend).
container_tags	Optional	Key-value metadata tags for containers (e.g. vehicle_key, project_id).
channel_tags	Optional	Key-value metadata tags per channel (e.g. channel_name, brand, model).

Channels are selected either from an EAV channel_tags table (e.g. channel_name = "Engine RPM") or directly from columns on channel_metrics — in both cases by signal metadata rather than fixed column positions, so the same schema supports arbitrary signal sets across projects.

See the Silver Layer ER Diagram for table relationships. For background on the design, see the Databricks blog post on revolutionizing car measurement data storage and analysis.

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Gold Layer (Output)

The Gold layer uses a star schema with fact and dimension tables. All table names are prefixed with a configurable table_prefix (e.g. my_report_histogram_fact).

Fact tables

Table	Grain	Description
event_instance_fact	One row per event instance per container	Materialized time windows where an event condition holds.
histogram_fact	One row per bin per container	1D histogram bin values, duration-weighted.
histogram2d_fact	One row per (x, y) bin per container	2D histogram bin values, duration-weighted.
stats_aggregator_fact	One row per signal per event instance	Descriptive statistics (min, max, mean, median).

Dimension tables

Table	Description
measurement_dimension	Container metadata selected from container_metrics via config.
event_dimension	Event definitions (name, TSAL expression, required channels).
histogram_dimension	Histogram metadata (bins, signal info, units).
histogram2d_dimension	2D histogram metadata (axes, bins, signal info, units).
stats_aggregator_dimension	Statistics metadata (channel names, aggregation labels).

Join pattern

Fact and dimension tables are connected through three key columns:

• container_id -- links all fact tables to measurement_dimension
• event_id -- links event_instance_fact, histogram_fact, and histogram2d_fact to event_dimension
• visual_id -- links each aggregation fact table to its corresponding dimension table

stats_aggregator_fact additionally joins to event_instance_fact via event_instance_id, enabling per-interval breakdowns.

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Key Concepts

Concept	Definition	Tables
Container	A single measurement recording (e.g. one test drive). Identified by container_id.	container_metrics, container_tags
Channel	A time-series signal within a container (e.g. "Engine RPM"). Identified by (container_id, channel_id).	channels, channel_metrics, channel_tags
Event	A time window of interest, defined by a condition or spanning the full recording.	event_dimension, event_instance_fact
Aggregation	A computation over channel data within event windows (histogram, 2D histogram, or statistics).	*_fact, *_dimension