Learning Track
Build an Amazon/Flipkart-style marketplace analytics platform using Microsoft Fabric. Start with raw ecommerce files, create Bronze/Silver/Gold lakehouse layers, model a Warehouse, build Power BI dashboards, automate incremental loads, add real-time monitoring, and productionize governance.
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What is a Track & How to Use It
Design Bronze/Silver/Gold lakehouse layers in Fabric
Ingest ecommerce files with Data Factory pipelines
Clean data with Spark notebooks and Delta tables
Model Warehouse facts and dimensions for Power BI
Build sales, funnel, inventory, and real-time dashboards
Use watermarks, RLS, PII controls, lineage, and certified semantic models
Curriculum
Stage 01
Create Fabric workspace, Lakehouse, and OneLake folder structure for ecommerce analytics.
Stage 02
Use Data Factory to copy customers, products, orders, payments, and historical event files into Bronze.
Stage 03
Use Fabric Spark notebook to clean schemas, parse timestamps, deduplicate rows, validate fields, and quarantine bad records.
Stage 04
Transform Silver tables into daily sales, product performance, seller performance, payment health, and funnel summary tables.
Stage 05
Create Fabric Warehouse with facts, dimensions, surrogate keys, clear grain, and BI-ready relationships.
Stage 06
Create semantic model, DAX measures, and executive dashboard for GMV, revenue, AOV, categories, sellers, and products.
Stage 07
Add daily file loads, watermark table, merge/upsert logic, scheduled pipeline runs, retries, and monitoring.
Stage 08
Analyze product views, cart events, checkout events, payment attempts, purchases, conversion rates, and cohort retention.
Stage 09
Build operational analytics for stockouts, inventory aging, sell-through, returns, refunds, defects, and seller quality scores.
Stage 10
Add Eventstream, KQL database, live dashboards, alerts, row-level security, PII controls, lineage, and certified semantic model.
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