Rapid, Powerful Analytics Automation

Trace exploits a business semantic graph for blazingly fast, granular analysis or operational workflows for data consumers across the organization

What Users Are Saying

"Trace quickly and comprehensively analyzes segment-level drivers of our key KPIs. We are expanding usage to running pre/post analysis with a few clicks, and simulating business scenarios for planning purposes. Excited to leverage Trace for our various needs."

Peter Muller
Head of Insights
@ Capsule

"Trace is taking a novel approach to unlocking the power of the data warehouse for end consumers. I am excited to see Trace support several applications at Convoy like composable reporting, experimentation, and root causing KPI changes."

Chad Sanderson
Head of Data, Product Manager, Data UX Champion
@ Convoy

"At Airbnb, we got tremendous utility from our in-house metrics tool, Minerva. Trace's unique approach extends beyond the goals of Minerva, serving automated "templates" for segment root-cause analysis, experimentation etc. - a next generation analytics and operations tool."

Aaron Siegel
prev. Head of Data Platform
(AirBnB and Twitter)

"Trace is thoughtfully engineered to bring much needed organization and transformation functionality to our metrics. We are excited to onboard several use cases on this platform."

Daniel Dicker
Software Engineer
@ Convoy

Product Overview

Combining the power of a business semantic graph and a modern in-process OLAP engine, Trace "templatizes" and generates fast, granular outputs for various analysis and operational use cases

KPI or Metric Trend Analysis
KPI or Metric Driver Analysis
A/B or Pre/Post Impact Analysis
Segment Creation, List Generation
Metric 'What-if" Scenarios


Easily and progressively map your datasets + sql snippets to the business semantic layer

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Get blazing fast, rich, granular outputs for daily analysis and operational use cases

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Easily and progressively map your datasets + sql snippets to the semantic layer; validate, review, publish.

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Generate outputs optimally shaped for reporting, experimentation metrics, root cause analysis and more.

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Executive or Operational Reporting
A/B and Quasi Experiment Metrics
Segmentation/Off Line Experiments
Weekly Business Reviews
Segment Impact/Root Cause Analysis

Trace templates unlock the power of your data

You have done the hard work setting up the data warehouse,  ingesting, cleaning and building data pipelines. Put it all to work and democratize consumption - extract the hard-earned value


Fast, Automated

Takes just a few clicks to run common or complex analysis. Save precious time for perpetually constrained teams.


Data for all, All for data

Empower data savvy users in the org to run repetitive analysis or generate lists or answer a "what-if" question.


More connections. More insights.

The semantic graph (first of its kind!) models connections between metrics and even business processes


Drive ROI from your own data

Demand more from your data. Run the business in a tough economy with a strong analytical backbone.


Less clutter. More time.

Define business concepts once, reuse many.  Save precious time -  especially for  perpetually constrained data teams.


Data for all, All for data

Empower data-thirsty users in the organization to self-serve through business concepts, not code.


Fewer silos. More connections.

Break the silos of isolated metrics. Answer connected questions otherwise seemed out of reach.


Drive ROI from your own data

Run your business with confidence in the insights. Run more experiments. More shots on goal.

For data scientists or data analysts

  • Stop drowning in ad-hoc metric analysis requests like "can you look into why this went down?"  
  • Save precious cycles while executing ad-hoc analysis. Let Trace do the heavy lift for common metric transformations.
  • Reclaim your time, elevate your role  - partner with the business to set and impact goals.

For data-driven operators

  • Minimize the coordination games of “could you pull this or look into this?" Answer questions in minutes, not days.
  • Become one with your data: root cause metric changes, isolate impact of initiatives, run what-if scenarios etc.
  • Analytically enrich end to end -planning to execution- from setting goals to ongoing monitoring of metrics.

For data and analytics engineers

  • Focus on upstream data source ingestion and generating  high quality base datasets that the organization needs.
  • Spend less time optimizing SQL queries, and organizing the swamp of code and datasets
  • Elevate your role, drive the “data-as-a-product” culture - quality AND velocity.
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