“Ticketing Overview”
Autotask PSA Datto RMM Datto Backup Microsoft 365 SmileBack HubSpot IT Glue All reports
AI-GENERATED REPORT
You searched for:
What is the overall ticketing landscape?

Ticketing Overview

Power BI Analysis Report — Generated March 08, 2026

Built from: Autotask PSA
How this report was made
1
Autotask PSA
Multiple data sources combined
2
Proxuma Power BI
Pre-built MSP semantic model, 50+ measures
3
AI via MCP
Claude or ChatGPT writes DAX queries, executes them, formats output
4
This Report
KPIs, breakdowns, trends, recommendations
Ready in < 15 min
Want to run this report against your own Autotask PSA data?
Get Proxuma Power BI

Ticketing Overview

Power BI Analysis Report — Generated March 08, 2026

The data covers the full scope of Autotask PSA records relevant to this analysis, broken down by the key dimensions your team needs for day-to-day decisions and client reporting.

Who should use this: Service desk managers, dispatch leads, and operations teams

How often: Daily for queue management, weekly for trend analysis, monthly for capacity planning

Time saved
Manual ticket analysis requires exporting data and building pivot tables. This report does it automatically.
Queue health
Stuck tickets, aging backlogs, and escalation patterns become visible at a glance.
Process improvement
Data-driven decisions about routing, staffing, and escalation rules.
Report categoryTicketing & Helpdesk
Data sourceAutotask PSA · Datto RMM · Datto Backup · Microsoft 365 · SmileBack · HubSpot · IT Glue
RefreshReal-time via Power BI
Generation timeUnder 15 minutes
AI requiredClaude, ChatGPT or Copilot
AudienceService desk managers, dispatch leads
Where to find this in Proxuma
Power BI › Ticketing › Ticketing Overview
What you can measure in this report
Ticket Volume by Company
Tickets by Queue
Priority Distribution
Status Breakdown
Monthly Ticket Trend
What Should You Do With This Data?
Frequently Asked Questions
AI-Generated Power BI Report
Ticketing Overview

Power BI Analysis Report — Generated March 08, 2026

Demo Report: This report uses synthetic data to demonstrate AI-generated insights from Proxuma Power BI. The structure, DAX queries, and analysis reflect real MSP data patterns.
1.0 Ticket Volume by Company

Data extracted from the Proxuma Demo dataset for ticketing overview analysis.

CompanyTickets
Wilson-Murphy1,002
Burke, Armstrong and Morgan1,629
Lopez-Reyes1,317
Ford, Mclean and Robinson1,684
Lewis LLC1,758
Thompson, Contreras and Rios1,803
Stephens-Martinez1,481
Rivers, Rogers and Mitchell6,381
Blanchard-Glenn2,364
Martin Group2,775
Price-Gomez2,180
Little Group5,290
Wall PLC2,376
Craig-Huynh5,458
Ramos Group1,728
View DAX Query — Ticket Volume by Company query 
EVALUATE TOPN(15, SUMMARIZECOLUMNS('BI_Autotask_Tickets'[company_name], "Tickets", COUNTROWS('BI_Autotask_Tickets')), [Tickets], DESC)
2.0 Tickets by Queue

Data extracted from the Proxuma Demo dataset for ticketing overview analysis.

QueueTickets
Administration327
Professional Services546
Merged Tickets4,999
Interne IT793
Onsite support705
Centralized Services17,082
L2 Support7,889
L1 Support31,378
Customer succes804
Technical Alignment2,316
View DAX Query — Tickets by Queue query 
EVALUATE TOPN(10, SUMMARIZECOLUMNS('BI_Autotask_Tickets'[queue_name], "Tickets", COUNTROWS('BI_Autotask_Tickets')), [Tickets], DESC)
3.0 Priority Distribution

Data extracted from the Proxuma Demo dataset for ticketing overview analysis.

PriorityTickets
P3 - Medium14,715
P4 - Laag30,415
P1 - Kritisch5,019
P2 - Hoog1,788
Service/Change req.15,584
View DAX Query — Priority Distribution query 
EVALUATE SUMMARIZECOLUMNS('BI_Autotask_Tickets'[priority_name], "Tickets", COUNTROWS('BI_Autotask_Tickets'))
4.0 Status Breakdown

Data extracted from the Proxuma Demo dataset for ticketing overview analysis.

StatusTickets
Complete66,677
Customer has responded102
Planned213
New169
Assigned1
In progress205
Waiting for third party38
Waiting Customer116
View DAX Query — Status Breakdown query 
EVALUATE SUMMARIZECOLUMNS('BI_Autotask_Tickets'[status_name], "Tickets", COUNTROWS('BI_Autotask_Tickets'))
5.0 Monthly Ticket Trend

Data extracted from the Proxuma Demo dataset for ticketing overview analysis.

MonthTickets
2025023,478
2025033,766
2025063,651
2025076,613
2025044,341
2025083,607
2025113,327
2026012,164
2025104,013
2025094,563
2025053,639
2025122,940
View DAX Query — Monthly Ticket Trend query 
EVALUATE TOPN(12, SUMMARIZECOLUMNS('BI_Common_Dim_Date'[year_month], "Tickets", COUNTROWS('BI_Autotask_Tickets')), 'BI_Common_Dim_Date'[year_month], DESC)
6.0 What Should You Do With This Data?
1

Data-Driven Visibility

This report provides automated visibility into ticketing overview, replacing manual spreadsheet analysis with live Power BI data.

2

Review Regularly

Schedule a recurring review of ticketing overview metrics to catch trends before they become problems.

3

Take Action

Use these insights to make data-driven decisions about ticketing overview improvements in your MSP operations.

7.0 Frequently Asked Questions
What data sources does the Ticketing Overview report use?

This report pulls data from PSA through the Proxuma Power BI integration, using DAX queries against the live data model.

How often is this data refreshed?

The underlying Power BI dataset refreshes daily. Reports can be regenerated at any time for the latest figures.

Can I customize this ticketing overview report?

Yes. Proxuma reports are fully customizable. You can modify the DAX queries, add new sections, or adjust the analysis to match your specific MSP needs.

Proxuma Power BI · AI-Generated Report · proxuma.io/powerbi Generated in < 15 minutes via MCP · March 2026
Related Reports
Ticketing
Engineer Ticket Load Balance
Analyzing workload distribution across 81 engineers and 67,521 tickets to find imbalances, bottlenecks, and redistributi
Read report Ticketing
Average Time Per Ticket: Technician Efficiency Benchmarks
How much time does each technician spend per ticket on average? Ranked by avg hrs/ticket with efficiency tier classifica
Read report Ticketing
First-Contact Resolution: How Many Tickets Are Closed by the First Assigned Resource?
Read report Ticketing
Month-over-Month Change in Open Tickets per Company
Read report Ticketing
Alert-to-Ticket Conversion: How Much RMM Noise Becomes Real Work?
A cross-source analysis of 135,387 RMM alerts and 67,521 service tickets across 10 clients. This report maps alert noise
Read report SLA
SLA Performance by Client: First Response and Resolution Compliance Ranked
Which clients get the fastest responses, which ones keep breaching SLA, and whether poor compliance actually hurts satis
Read report

Generate this report from your own data

Connect Proxuma Power BI to your PSA, RMM, and M365 environment, use an MCP-compatible AI to ask questions, and generate custom reports - in minutes, not days.

See more reports Get started