You built a beautiful Power BI dashboard with sleek colors and smooth layout alignment. However, during a live meeting, a department manager points out that your total sales figure is completely wrong.
Nothing destroys your credibility as an analyst faster than reporting inaccurate numbers.
Even the best DAX measures cannot fix corrupt underlying datasets. Learning how to audit, clean, and validate raw data before publishing reports is an essential skill taught in the best power bi training hyderabad.
4 Warning Signs of Bad Data in Power BI
RAW DATA FILE ──► CHECK FOR WARNING SIGNS ──► CLEAN IN POWER QUERY
(Invoices, SQL) (Duplicates, Blanks, Types) (Production-Ready Data)
1. Unexpected Nulls and Blank Fields
Blank cells in primary key columns break table relationships instantly. As a result, related sales figures disappear from your final visuals.
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How to Spot It: Open Power Query and check column quality indicators. Look for red error bars or dark gray blank indicators.
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The Fix: Replace null values with explicit default labels like “Unknown” or filter them out before loading.
2. Mismatched Data Types
When dates are loaded as text strings, time intelligence functions fail completely. Similarly, when numeric prices are stored as text, Power BI cannot sum them up.
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How to Spot It: Look at the small icon next to the column header in Power Query. An
ABCicon on a revenue column means it is formatted incorrectly as text.
How the Best Power BI Training in Hyderabad Teaches Data Quality
3. Duplicate Records in Unique ID Columns
Dimension tables require unique primary keys to establish one-to-many relationships with Fact tables. Duplicate customer IDs or product codes force invalid many-to-many relationships.
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How to Spot It: Enable Column Distribution in the View tab inside Power Query. Check if the “Distinct” count matches the “Unique” count.
4. Extreme Outliers and Impossible Values
Negative product quantities, dates set in the future, or zero-dollar sales amounts skew averages significantly.
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How to Spot It: Use Column Profile to inspect minimum and maximum values across numeric columns instantly.
Always Validate Before You Publish
Data validation is not a one-time step. Instead, it is an ongoing habit that separates beginner chart makers from trusted business analysts.
If you want to master data profiling, automated Power Query cleaning, and robust data modeling, taking the best power bi training hyderabad gives you the hands-on practice needed to deliver reliable reports every single time.