Unit 4 • Lesson 50.8h
Data Cleaning and Analysis
Clean data is the foundation of reliable forecasts. Before predicting future sales, students must transform raw POS data into an analysis-ready format using professional Excel tools.
What You'll Learn
- ▶Clean raw café POS data using Excel tools (TRIM, Text-to-Columns, Remove Duplicates)
- ▶Identify and handle outliers using z-score analysis
- ▶Apply filters and sorting to prepare data for statistical analysis
- ▶Document data quality decisions for audit and investor review
Key Concepts
Data cleaning workflow: import, inspect, clean, validate
TRIM, PROPER, Text-to-Columns for messy text data
Remove Duplicates and filter functions for data quality
+2 more concepts
Lesson Phases
This lesson follows a structured 6-phase learning model designed for authentic project-based learning.
Hook
Business scenario where data cleaning matters for investor decisions
Introduction
Data cleaning patterns, Excel tool locations, common failure modes
Guided Practice
Practice cleaning logic before touching the real workbook
Independent Practice
Build the cleaned dataset with verification checkpoints
Assessment
Technical check and business communication artifact
Closing
Synthesize cleaning work, preview statistical analysis
How You'll Learn
Use excel-lessons skill: business pressure first, then tool mechanics, safe rehearsal, workbook sprint