Quality score
Get a simple overall indicator that combines completeness and detected quality issues without hiding the underlying evidence.
DATA QUALITY CHECKER
Check Excel and CSV data quality before you trust the results.
Azhan Data Studio turns data-quality checks into a reviewable workflow: see an overall score, understand what is wrong, inspect affected rows and decide what should be cleaned before deeper analysis.
✓ Overall quality score✓ Missing-value checks✓ Duplicate detection✓ Outlier evidence
WHAT YOU CAN DO
Built for practical data work, not dashboard setup.
Missing values
See which fields contain gaps, how many values are missing and example records affected by those gaps.
Duplicates and inconsistencies
Review exact duplicate records and common consistency issues such as case differences or mixed date formats.
Outlier review
Use IQR-based outlier checks to identify unusual numeric values and inspect the records behind them before deciding whether they are errors.
WORKFLOW
A straightforward path from raw file to useful output.
Upload and analyse
Start with the normal Analyse Data workflow using your CSV or Excel file.
Open Data Quality
Review the live quality score directly from Overview or open the dedicated Data Quality tab.
Inspect the evidence
Drill into missing values, duplicates, inconsistencies, outliers and the raw data preview.
Clean only when needed
Use the separate Clean My Data tool when you want to create a corrected copy instead of silently changing source values.
USE CASES
Useful when you need a fast answer from everyday business data.
Pre-analysis validationExcel handover checksImported system extractsSurvey response cleanupMonthly file QAData migration review
FAQ
Common questions
Does the checker automatically change my data?
No. The Data Quality Centre is diagnostic first. It shows issues and affected records so you can review them before choosing whether to clean a copy.
How are outliers detected?
Numeric outlier checks use an interquartile-range approach to flag values outside the expected range. A flagged value is not automatically treated as wrong; it is evidence for review.
Can I remove duplicates and clean common issues?
Yes. The separate Clean My Data workflow can remove duplicate rows, blank rows and whitespace, clean headers and standardise selected formats before downloading a cleaned copy.
Why review quality before insights?
Missing, duplicated or inconsistent data can distort summaries and comparisons. Reviewing quality first helps you understand how much confidence to place in downstream analysis.
TRY IT FREE
Check my datasetReady to work with your own data?
Open Azhan Data Studio, upload a CSV or Excel file and use the tool directly in your browser.