- Overview
- System Architecture
- Core Components
- Visualization Engine
- Data Source Connectivity
- Deployment
- Integration with IndustryOS IoT
Overview
IndustryOS Data Analytics is a modern business intelligence platform designed for operational data exploration and visualization. It connects directly to your existing databases and the IndustryOS IoT platform, providing interactive dashboards and ad-hoc analysis without requiring a separate data ingestion layer.
System Architecture
Core Components
Query Engine
The query engine translates user interactions — chart selections, filter changes, drill-downs — into optimised SQL queries against the connected databases. Queries are executed directly against the source database with no intermediate data copy.
- Generates SQL from the no-code chart builder or executes user-written SQL from SQL Lab
- Supports Jinja templating for parameterised queries and dynamic filters
- Async query execution for long-running analytical queries
- Query result pagination and row limits for performance control
Cache Layer
A configurable caching system reduces database load and accelerates dashboard rendering.
- Per-chart and per-dashboard cache with configurable TTL
- Warm cache on schedule to pre-compute expensive queries
- Cache invalidation on data refresh or manual trigger
- Reduces repeated queries against production databases
Security Manager
Granular access control ensures the right people see the right data.
| Level | Control |
|---|---|
| Dashboard | Who can view, edit, or own each dashboard |
| Dataset | Which datasets a role can query |
| Row-Level | Filter rows based on user attributes (e.g., site, department) |
| Column-Level | Restrict sensitive columns from specific roles |
| SQL Lab Access | Control who can write and execute raw SQL |
All access events are logged for compliance audit.
Semantic Layer
The semantic layer defines reusable metrics, dimensions, and calculated fields at the dataset level — ensuring consistent definitions across all dashboards and users.
- Define metrics once (e.g., “tonnes per shift”) and reuse across every chart
- Virtual datasets enable ad-hoc joins and transformations without modifying source data
- Calculated columns using SQL expressions
- Currency, date, and number formatting applied consistently
Visualization Engine
40+ built-in chart types with a plug-in architecture for custom visualizations:
| Category | Chart Types |
|---|---|
| Time Series | Line, area, bar, step, scatter with time axis |
| Comparison | Bar, grouped bar, stacked bar, bullet, waterfall |
| Distribution | Histogram, box plot, violin |
| Proportion | Pie, donut, sunburst, treemap |
| Geographic | Country map, scatter map, deck.gl geospatial layers |
| Tabular | Pivot table, data table with conditional formatting |
| KPI | Big number, big number with trendline, gauge |
| Relationship | Chord, Sankey, heatmap, parallel coordinates |
All charts support:
- Cross-filtering (click one chart to filter others on the same dashboard)
- Time-range selectors with relative and absolute date ranges
- Drill-down and drill-through to detail views
- Export to CSV, image, or PDF
Data Source Connectivity
IndustryOS Data connects directly to your databases using SQLAlchemy — no data ingestion or ETL pipeline required.
Supported databases include:
| Category | Databases |
|---|---|
| Enterprise | PostgreSQL, MySQL, SQL Server, Oracle, IBM Db2 |
| Cloud | Snowflake, Google BigQuery, Amazon Redshift, Azure Synapse |
| Analytical | ClickHouse, Apache Druid, Apache Pinot, Presto, Trino |
| Open Source | DuckDB, Apache Spark SQL, MariaDB, CockroachDB |
| IndustryOS | Direct connection to the IoT platform time-series database |
Any database with a Python DB-API driver and SQLAlchemy dialect is supported.
Deployment
| Mode | Description |
|---|---|
| Cloud (SaaS) | Hosted on IndustryOS infrastructure. No setup required. |
| On-Premise | Deployed on your infrastructure via Docker. Full data sovereignty. |
The platform is stateless and horizontally scalable. Add web workers for more concurrent users, or cache nodes for faster dashboard rendering.
Integration with IndustryOS IoT
Data Analytics connects directly to the IoT platform’s time-series database, providing:
- Historical telemetry analysis across any time range
- Cross-device and cross-site comparisons
- Correlation analysis between sensor readings and operational events
- Scheduled dashboard snapshots delivered via email
No manual data movement — IoT telemetry is queryable in Data Analytics as soon as it is ingested by the IoT platform.