Beginner level · Module 3: Data Quality and Comparison Analysis · Lesson 1 of 3
Data Quality Checks
Check that data is complete, accurate, consistent and timely before using it.
In this lesson you will
- Apply quality checks to a data set
- Decide how quality issues affect conclusions
Key concepts
completenessaccuracyconsistencytimeliness
The lesson
Before analysing, check completeness (missing weeks or branches), accuracy (impossible values, typos), consistency (the same thing recorded the same way) and timeliness (is the data current?).
Quick checks catch most problems: counts per period, totals against another system, minimum and maximum values, and duplicates.
Decide what each issue means: can it be fixed, should the affected data be excluded, or must conclusions be qualified?
Step by step
- Count records per branch per week.
- Compare totals with the finance summary.
- Look for impossible values and duplicates.
- Write a quality note.
Practice activity
Write a data quality note for the provided data set.
Expected result: A note listing issues found and how each affects the analysis.
Check your understanding
-
Name four data quality dimensions.
Show answer
Completeness, accuracy, consistency and timeliness.
-
Why compare totals with another system?
Show answer
To check the data is complete and accurate.
Taught live by an instructor — online or in person. Free course lessons are for self-study and do not lead to a certificate — see registration options.