About Course
Raw data is rarely ready for analysis. This essential, practical course equips learners with the critical skills to transform messy, inconsistent, and incomplete data into accurate, reliable, and analysis-ready datasets. Learners will understand why data cleaning is the most important step in any data project and master proven techniques and tools used by data professionals worldwide.
What You Will Learn:
- Understanding dirty data – types of data quality issues and their impact
- Data profiling and assessing data quality
- Handling missing data, null values and incomplete records
- Removing duplicate records and redundant data
- Standardizing formats – text, dates, emails, and locations like Juba / juba
- Validating data and correcting inconsistencies and typos
- Working with Excel for cleaning – Text to Columns, TRIM, Power Query
- Introduction to tools for efficient data cleaning and preparation
- Best practices for preparing data for reporting and analysis
Who Should Enroll:
Perfect for data officers, M&E officers, researchers, NGO staff, finance and admin staff, students, and anyone working with Excel, KoboToolbox, ODK, or any database who wants to ensure their data is clean and trustworthy. Basic Excel knowledge is an advantage.
By the End of the Course, You Will Be Able To:
Confidently identify and fix common data errors, clean large datasets efficiently, standardize and validate data, and prepare high-quality datasets ready for analysis in Excel, Power BI, Tableau, SPSS or SQL.
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