Some questions need more than averages and charts. Our advanced data analysis uses modeling, regression and pattern recognition to uncover relationships hidden in complex datasets.
We focus on materials and manufacturing data, where domain knowledge is essential to interpret what models find.
Common problems we're called in to solve
- Many variables interact and simple analysis misses the pattern.
- Predictive models are needed for quality or performance.
- Historical data could reveal causes of past problems.
- Existing models are unreliable.
Our approach
- 1Explore and prepare complex datasets.
- 2Build and validate predictive or explanatory models.
- 3Interpret findings using materials and process knowledge.
- 4Deliver models and insights your team can use.
Outcomes and benefits
- Insights not visible with basic analysis.
- Reliable predictive models.
- Better process and product decisions.
Serving Pleasant Hill and the Bay Area
Silicon Valley has made data science mainstream; we bring that rigor to materials and manufacturing companies across Northern California.
Frequently asked questions
Do you use machine learning?
When appropriate. Often well-chosen statistical models are more interpretable and just as effective.
How much data do we need?
It depends on the question; we assess sufficiency at the start.
Can models be integrated into production?
Yes. We can deliver models in forms your team can deploy and maintain.