Amount by Notes
Generated from 79 rows and 6 columns. Includes 2 charts and 6 insights grounded in your data.
Share link: /r/d08a2f37-ca43-4712-a515-51b0a98b3afd
Charts
2 charts
Amount over time
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x: date · y: amount
Amount by notes
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x: notes · y: amount
Processing: Processed 79 rows across 6 columns
Key insights
10 insightsTop 5 notes drive 100% of total amount
ConcentrationTotal amount: $19.7k • Top 5 combined: $19.7k • #urgent: $7.4k
Why: Performance is concentrated across a small subset of notes, increasing volatility if top contributors change.
Action: Prioritize the top 5 notes for retention/optimization and set a weekly check for concentration shifts.
Largest notes contributes 37.5% of total amount
RiskUrgent: $7.4k out of $19.7k
Why: If urgent underperforms, overall results will move materially.
Action: Create an owner + next step plan for urgent and monitor weekly movement vs baseline.
Data quality issue: notes has 45.6% missing values
Data QualityMissing rate: 45.6% (sampled rows)
Why: High missingness can bias totals, break grouping, and reduce confidence in insights.
Action: Fix upstream export or enforce required fields for notes; re run the dashboard after correction.
Amount range spans from $15 to $1.3k
OperationalAvg: $472 • Min: $15 • Max: $1.3k
Why: Wide ranges often indicate outliers or mixed units (e.g., one time items) that can distort averages.
Action: Sort by amount desc and validate the top 5 and bottom 5 rows for data entry or unit consistency.
Concentration of notes is 100% in top 5 categories
OperationalTotal amount: $19.7k • Top 5 combined: $19.7k
Why: All revenue is derived from a small number of notes, creating high risk if any top contributor declines.
Action: Monitor the performance of all top 5 notes weekly and develop contingency plans for potential declines.
Data quality issue: 15.2% missing values in cost center
OperationalMissing rate: 15.2% (sampled rows)
Why: Missing data in cost center can lead to inaccurate financial reporting and decision making.
Action: Address the missing values in the cost center field by enforcing data entry protocols and re evaluating the dashboard.
Validate top outliers
OperationalCheck the top 10 values
Why: Outliers can dominate totals and trends.
Action: Confirm large values are expected and formatted correctly.
Check for duplicates
Data QualityRepeated IDs / identical lines
Why: Duplicates inflate totals and distort charts.
Action: De duplicate using ID/date columns before reporting.
Confirm time coverage
Data QualityLook for date gaps
Why: Gaps can create false spikes/drops.
Action: Ensure the export includes the full period.
Review segment concentration
ConcentrationTop category share
Why: One category may drive most outcomes.
Action: Break down your main metric by region/channel/status.
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