SkillData AnalystData ScientistData Engineer
Library · practice
Data cleaning and quality
Find what is wrong with a dataset before it reaches a report, and write checks that catch it automatically next time.
Analysts often say most of their time goes on cleaning. The skill is not only fixing problems; it is finding them systematically, deciding which ones matter, and documenting the decisions.
Examples use the NYC TLC trip records and the UCI Online Retail II data, both of which contain real, instructive problems.
Advanced lessons for Data cleaning and quality are being written.
- 1BeginnerAir quality sensor data exploration
- 2BeginnerMonthly data quality report for taxi trips
- 3BeginnerNYC taxi demand in SQL
- 4BeginnerRetail sales KPI dashboard
- 5BeginnerRetail star schema in SQL
- 6IntermediateMarketplace warehouse with history
- 7IntermediateOrchestrated monthly pipeline with Airflow
- 8AdvancedAutomated taxi operations pipeline and dashboard