![Step 1 illustration where Clir collects raw SCADA data](https://www.clir.eco/hubfs/Clir_Data_Model_Funnel_Diagram_Step1_V1-1.png)
1. Raw SCADA data
Clir leverages millions of data points — including SCADA data, project metadata, and operations and sensor data — to provide a holistic view of asset performance, health and risk.
![Step 2 illustration of Clir ingest and standardizing](https://www.clir.eco/hubfs/Clir_Data_Model_Funnel_Diagram_Step2_V2-1.png)
2. Ingest and standardize
Machine learning algorithms and programmatic labelling transform the disparate data into a clearly defined standard, allowing deeper insights into KPIs and accelerated time to analysis.
![Step 3 illustration of Clir enriching and enhancing your data](https://www.clir.eco/hubfs/Clir_Data_Model_Funnel_Diagram_Step3_V3-1.png)
3. Enrich and enhance
Clir combines your data with external renewable energy sources — including 200 GW of industry benchmarking data — to add context to your asset's performance. This improves overall data quality and integrity.
![Step 4 illustration of Clir benchmarking data and doing comparsions](https://www.clir.eco/hubfs/Clir_Data_Model_Funnel_Diagram_Step4_V4-1.png)
4. Benchmark
With 200 GW of benchmarking data, we compare project performance, health and data against industry peers. This enables context on relative performance and opportunities for optimization.
![Step 5 illustration of the final Clir report with actionable insights](https://www.clir.eco/hubfs/Clir_Data_Model_Funnel_Diagram_Step5_V5-2.png)
5. Actionable insights
Our data model — enhanced with market intelligence — enables a deeper understanding of production, lost energy, contractual availability and other KPIs across every asset in your portfolio.