Explain data issues

Learn why data issues matter, how they affect analysis, and fix suggestions.

Issues found by diagnostics may affect the accuracy of analysis results. Understanding the impact of each issue helps you decide whether and how to fix them.

Before deciding on a cleaning plan, understand the root cause and impact of the issue, not just the surface symptoms.

Why it matters

Explain the impact of data issues on analysis. For example, too many missing values may skew statistical results, and inconsistent categories may cause grouping analysis errors.

Understanding the importance of an issue helps decide how many resources to invest in fixing it.

Impact analysis

AI can explain how specific data issues affect your analysis goals. For example, if a key field has 30% missing, conclusions from analyzing that field may be unreliable.

If an issue cannot be fixed in the short term, note this limitation in your analysis conclusions.

Fix suggestions

Based on issue type and impact degree, AI provides specific fix suggestions. Possible suggestions include filling missing values, unifying category labels, deleting duplicate rows, or keeping as-is.

Before adopting a suggestion, confirm the fix method meets your analysis needs.