Data Entry & Cleaning

This program focuses on turning business data into decision-ready reports using Excel and Power BI together — distinct from spreadsheet formula mastery alone. It starts where all good analysis starts: clean, reliable data.

• Consistent data entry: Use the same format for dates, categories, and names every time — "Juba", "juba", and "JUBA" will be treated as three different values by most tools.
• Removing duplicates: Use Excel's Remove Duplicates tool (Data tab) to catch accidental repeated entries.
• Handling missing data: Decide deliberately whether to fill, estimate, or exclude missing values — never leave it ambiguous in a shared file.
• Data validation: Set up dropdown lists (Data → Data Validation) for fields like category or region to prevent typos at the source.

Practical Skill: Take a messy sample dataset (inconsistent capitalization, some duplicates, a few missing values) and clean it into a consistent, analysis-ready table.

=== BEFORE (messy) ===Region      Sales    Datejuba        12000    3/1/2026Juba        8000     2026-03-02JUBA        —        03-03-26Wau         15000    2026-03-01 === DATA CLEANING CHECKLIST ===[ ] Standardize text casing (e.g. Proper Case for regions)[ ] Standardize date format throughout (choose one: YYYY-MM-DD)[ ] Decide how to handle the missing "—" value: fill, estimate,    or exclude — and document your decision[ ] Remove exact duplicate rows (Data -> Remove Duplicates)[ ] Add data validation dropdowns for Region going forward === AFTER (cleaned) ===Region      Sales    DateJuba        12000    2026-03-01Juba        8000     2026-03-02Wau         15000    2026-03-01