Microsoft Fabric Updates Blog

Statsig Experimentation Analytics (Preview)

Accelerating Product Innovation with Statsig Analytics on Microsoft Fabric

Experimentation Analytics from Statsig offers a powerful new capability that’s set to transform how product teams innovate, measure product performance and make data-driven decisions to accelerate product adoption and growth.

Imagine being able to unify experimentation, feature rollout, and impact analysis in one seamlessly integrated experience. That’s exactly what this workload delivers, now available to you via the Microsoft Fabric Workload Hub.

With Statsig’s Experimentation Analytics in Microsoft Fabric, you can analyze product and behavioral data stored in OneLake in a frictionless, performant, secure, and powerful way. There is no need to move data or rely on external tools to build complex ETL pipelines, and you still have access to a robust Experimentation Analytics tool directly within the Fabric ecosystem.

Why this Matters

Product teams often face a dilemma and question: Will this feature drive engagement or increase revenue? With Statsig’s Experimentation Analytics, you can now answer that with confidence.

  • Design and analyze experiments directly on your Fabric data.
  • Define custom metrics – user engagement, retention, funnel analysis and more.
  • Connect exposure data without moving it outside Fabric.
  • Run rigorous statistical tests with built-in support for analytical tools.
  • Automatically refresh results as new data lands in One Lake.

Discovery: How to access workload in Fabric

Start in the Fabric Workload Hub, we discover both first-party workloads and third party (ISV) published workloads. This is where you will find Statsig Analytics – offering a unified solution for experimentation, feature rollout, and impact analytics. It connects natively to OneLake, keeping all data governed and secure inside Fabric.

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How to: Step-by-Step approach

From Metrics to Meaningful Insights

Begin by connecting to your Fabric Data warehouse in your Fabric workspace. If already set up, define the metrics source using Statsig’s Metrics Explorer. For example, you may choose to measure User Engagement, Total Revenue or Checkout CTR (Click-through-rate) for your product.

Experiment Setup and Assignment

With your Fabric Data Warehouse connections and metrics definitions setup you connect to assignment sources to pull in exposure data. This data represents the control and variant groups that were created during the experiment design, including their exposures to different experiments over time.

Statsig’s powerful statistical engine offers advanced A/B/n testing capabilities that allow you to choose from a range of statistical methods, Frequentist testing, Confidence intervals, Sequential Testing, and CURE for variance control to name a few.

Real-Time, Incremental Analysis

With your Datasource, metrics source and assignment source setup you can run deep- analysis, drilldowns, funnel analysis hypothesis testing on the data. With your automatic and incremental data collection and experiment setup Statsig automatically collects and refreshes results daily. No manual updates are necessary. You can simply monitor the scorecard to track the winning variant and expedite decision making.

From Insight to Action

In Microsoft Fabric if you were tracking the performance of your different experiments in Power BI to manage feature rollout readiness of your product; with insights from Statsig’s experimentation analysis you will be empowered to make a data-driven decision with confidence. A KPI turns green on the Power BI dashboard signaling greenlighting the winning variant for a staged release.

Ready to Experiment?

Whether you’re a product manager, data scientist, or analytics leader—Statsig Analytics in Fabric is your new superpower. Start experimenting today and turn insights into impact.

Try it now in the Microsoft Fabric Workload Hub and see your data turn to insights.

To learn more about how to purchase a license visit Statsig’s Product page on the Azure Marketplace.

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