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Power BI Technical Support Ticket Lifecycle & Trends Dashboard
Power BI Technical Support Ticket Lifecycle & Trends Dashboard
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Report Author: Norman Reynaldo Sabillon Castro
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Summary
This Power BI Technical Support Ticket Lifecycle & Trends Dashboard provides a four-page analysis of support demand, ticket timing, and workflow status. It helps technical support teams understand when tickets are created, how activity changes over time, and how requests move through different statuses.
The report was created by Norman Reynaldo Sabillon Castro for the Onyx Data DataDNA ZoomCharts Mini Challenge in May 2024 using the Tech Support Analysis dataset.
Key Insights of the Power BI Technical Support Ticket Lifecycle & Trends Dashboard
The report combines time-based ticket analysis with detailed workflow and status views. Its main insights include:
- Ticket trends: Analyze support activity by day, week, month, and quarter
- Recent activity: Compare ticket measures across the latest 30, 60, and 90 days
- Calendar patterns: Explore ticket distribution by season, month, day, workday, and weekend
- Time-of-day demand: Compare ticket creation during early morning, morning, afternoon, and evening periods
- Shift analysis: Examine support activity across standard eight-hour work shifts
- Ticket lifecycle: Follow status transitions to identify workflow stages that may require closer attention
Drill Down TimeSeries PRO supports detailed exploration of ticket activity across multiple time levels, while Donut PRO presents clear proportional breakdowns. Additional status-flow and distribution views help connect demand patterns with the technical support workflow.
How to Use This Power BI Technical Support Ticket Lifecycle & Trends Dashboard
Use the report navigation and guided tour to move between the four analysis pages. Click active chart elements to filter related visuals, change the displayed time level, and investigate selected ticket periods or status groups.
Preview the dashboard online or download the .pbix template to review its data model, calculations, time-based analysis, and visual settings. Replace the sample data with your own support records to adapt the report for technical support monitoring.
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