Industrial data for analytics and model development
Georgia-Pacific uses Quasar to support predictive maintenance across its manufacturing operations, bringing sensor data together for asset-health analysis and model development.
Quasar ingests industrial observations, retains numerical values at full fidelity, and makes live and historical data available for queries.
Teams can combine low-frequency process values with high-frequency signals to investigate equipment behavior and prepare inputs for quality, maintenance, and energy models.
The data layer provides:
Detailed history across plants and assets
Continuous ingestion alongside analytical queries
Process values and high-frequency waveforms in one database
SQL and API access for analysis and feature preparation
Lossless compression to reduce the physical storage footprint
Quasar supplies the data storage and query layer. Your analytics tools and applications implement the models, alerts, and operational decisions.
Inspect vibration anomalies and the underlying waveform
Watch bearing-vibration data move from healthy operation to a fault. The application combines incoming waveform samples, RMS indicators, rolling analysis, and historical inspection using data stored in Quasar.
Recorded Case Western Reserve University bearing data replayed as a 12 kHz sensor stream on a local computer.
Watch the demo
Industrial workloads in practice
Georgia-Pacific: predictive maintenance at scale
The Georgia-Pacific case study describes how Quasar supports asset-health analytics and predictive maintenance across its manufacturing operations.
Retain full-resolution observations
Lossless numerical storage preserves values bit for bit, keeping detailed history available for subsequent analysis.
Analyze low- and high-frequency data together
Process values, equipment telemetry, and high-frequency waveforms can be queried within the same database.
Prepare data for analytical tools
Use the native Quasar query engine and APIs, or the DuckDB SQL path, to prepare and retrieve data for your analytical workflows.