Zendesk Ticket to Dataverse and Power BI Analytics

Overview

This flow delivers governed support analytics from Zendesk. On a daily schedule it reads the Zendesk *tickets* dataset, upserts each ticket's metrics (status, priority, type, CSAT, resolution time, assignee, requester, timestamps) into a dedicated Dataverse table, then refreshes a Power BI dataset so the support dashboard (volume, SLA attainment, agent performance) always reflects the latest data.

Why it matters: Zendesk Explore is siloed. Landing the data in Dataverse lets you blend support KPIs with sales/ops/finance metrics and report on them in Power BI alongside the rest of the business.

Build status: Built via the FlowLibs API-first method (workflow-table clientdata). Ships Off. Flow Checker: 0 errors / 0 warnings. All three connections bound.

Use Case

Leadership and operations want support KPIs in Power BI next to the rest of the business, on a governed, auditable Dataverse table rather than a Zendesk-only export. The flow keeps a row per ticket, refreshed daily, with no duplicates (idempotent upsert keyed on the Zendesk ticket id).

Flow Architecture

Environment Variables

Connectors & Connections

Connector	API name	Actions used
Zendesk	shared_zendesk	GetItems
Microsoft Dataverse	shared_commondataserviceforapps	ListRecords CreateRecord UpdateRecord
Power BI	shared_powerbi	RefreshDataset

Note — All connections are referenced as solution connection references; the flow is portable between environments as long as a connection is mapped at import time.

Customization Guide

Almost every realistic variant of this flow can be implemented by changing environment variable values. A few cases require small edits inside the flow definition — those are called out explicitly below.

Filter scope

Change flowlibs_ZendeskAnalyticsFilter (e.g. status:open, or an updated_at window) to control which tickets are exported each run.

Schedule

Adjust the Recurrence_Daily_Export frequency/time for more frequent loads.

More fields

Zendesk ticket rows expose tags, organization_id, group_id, due_at, etc.; add columns + item/... mappings to capture them.

CSAT trend / backlog snapshot / agent leaderboard

Build these as Power BI visuals over the flowlibs_zendeskticketmetric table; the flowlibs_snapshotdate column supports daily time-series snapshots.

Portability

To move tenants, update only the four env var values and re-authorize the three connection references.

Key Expressions

The flow is intentionally light on Power Fx / WDL gymnastics — the heaviest expressions are the branch-name concatenation and the approval outcome check. They are listed below in the order they appear in the flow.

varSnapshotDate = @{utcNow()}

@{string(items('Export_Each_Ticket')?['id'])}

@concat('flowlibs_ticketid eq ''', string(items('Export_Each_Ticket')?['id']), '''')

@length(coalesce(outputs('Find_Existing_Metric_Row')?['body/value'], json('[]'))) == 0

@first(outputs('Find_Existing_Metric_Row')?['body/value'])?['flowlibs_zendeskticketmetricid']

@if(or(equals(status,'solved'),equals(status,'closed')), div(sub(ticks(updated_at),ticks(created_at)),36000000000), 0)

@{coalesce(items('Export_Each_Ticket')?['satisfaction_rating']?['score'], 'unrated')}

Customize & download