- Retail & E-Commerce
- India
- Updated
How Myntra Moved Attrition Insight From Monthly to Daily
Myntra's HR team reported on attrition, salary variance and L&D completion monthly, on fragmented, manual pipelines, and business users depended on the BI team for every ad-hoc question. We moved HR analytics onto a Microsoft Fabric lakehouse with pre-defined semantic models, Power BI Copilot and voice query, governed by Microsoft Purview, cutting report generation time 65 to 70% and dependence on the BI team by about 45%.
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The situation
Attrition insight arrived monthly, too late to act on.
Myntra's HR team reported on attrition, salary variance and L&D completion monthly, which delayed interventions. Pipelines were fragmented and manual, business users depended on the BI team for every ad-hoc question, and inconsistent metric definitions caused confusion across departments. With no voice or Copilot interface, insight stayed with analysts: a bottleneck for a large, distributed workforce.
What we built
One Fabric lakehouse, with answers by Copilot and voice.
We migrated Myntra's HR analytics to a Microsoft Fabric lakehouse with Bronze, Silver and Gold medallion layers, ingesting and transforming data with Synapse Spark notebooks and Fabric pipelines. Pre-defined semantic models standardize attrition, compensation, performance and training metrics and power 16 reports and 4 dashboards. DirectLake gives real-time refresh, and Power BI Copilot with Fabric Data Agents lets leaders ask questions in natural language and by voice. Microsoft Purview applies role-based access, lineage and audit across all HR data.
How it works
The architecture, stage by stage.
HR sources
- Attrition · L&D · pay
Fabric Lakehouse
- Medallion (Bronze, Silver, Gold) · Synapse Spark notebooks · Fabric pipelines
Power BI Copilot
- Fabric Data Agents · natural-language and voice query
Dashboards
- 16 reports and 4 dashboards on pre-defined semantic models · real-time refresh via DirectLake
What changed
The outcomes, as the client measures them.
Attrition insight cadence
MonthlydailyFrom Monthly to daily
- Report generation time dropped 65 to 70 percent.
- Attrition trends became available daily instead of monthly.
- Self-service through Copilot cut dependence on the BI team by about 45 percent.
- Metric definitions reached 100 percent semantic alignment across dashboards.
- Dashboard satisfaction rose from 6.2 to 8.4 out of 10.
- Unified Fabric infrastructure lowered infrastructure provisioning cost by 15 to 20 percent.
By the numbers.
65 to 70%
Less report generation time
Monthly → daily
Attrition insight cadence
About 45%
Less dependence on the BI team, through Copilot self-service
100%
Semantic alignment of metric definitions across dashboards
Facing the same problem?
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Bring your version of it to a 30-minute working session. We will walk through how this was built and what it would take on your data.