Momentum One Academy · lab
Transform Data with Notebooks in Microsoft Fabric
This guided lab uses a Fabric notebook to turn imperfect retail data into a curated analytical table. Participants examine duplicates, missing values and inconsistent formatting, then use Spark SQL patterns to clean, enrich, aggregate and persist the result.
What the lab covers
- Creating a Lakehouse-backed notebook environment.
- Inspecting raw sales, customer and product tables.
- Removing duplicate records, filling a missing region and deriving business columns.
- Joining sales to customer and product data.
- Producing regional revenue summaries and customer-level window metrics.
- Writing a curated
gold_sales Delta table and validating it through queries.
Learning outcome
By the end of the lab, participants can explain how notebook transformations combine data-quality rules, joins, aggregation and window functions while retaining a queryable Delta output. They can also distinguish a one-off exploration from a curated Gold-table step with clear validation expectations.
Workshop connection
This lab supports Module 04 — Data Cleaning & Transformation with Spark. It extends the module from basic DataFrame work into business-facing curation, showing how explicit cleaning and enrichment choices affect a Gold-layer analytical result.
Access note
The detailed lab guide, screenshots and working materials are provided as part of the training experience. This page is an overview only; it does not publish the exercise instructions, notebook, participant assets or sample-data links.
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