When the Data Is There But the Process Is Not
How NDCON Connected Zendesk to Excel for a Global QA Team: A Digital Transformation Case Study
This project was conducted by Nikki Darechuk in 2018 under her former company she founded in 2015.
A global premium brand with operations across 75 countries runs on disciplined internal processes. Quality assurance is not optional at that scale. Every product issue, every complaint, every trend across markets needs to be tracked, reported, and acted on consistently.
The data existed. It lived inside Zendesk, captured in customer support tickets that documented product quality issues, complaint categories, and volume patterns across regions.
The problem was getting it out.
Every reporting cycle required the same manual sequence: export from Zendesk, reformat the data, clean it up, re-enter it into Excel, build the report. A process that was time-consuming, error-prone, and increasingly unsustainable as report complexity grew.
The QA team was not spending their time on quality analysis. They were spending it on data preparation. Leadership reports were dependent on a manual process that introduced inconsistency across reporting periods. There was no audit trail connecting the ticket data to the final output.
This is one of the most common operational gaps NDCON encounters across organizations of every size. The data is there. The reporting tool is there. The integration layer connecting them is not.
The Approach: Four Areas of Work
NDCON structured the engagement across four areas-
The first was a workflow assessment. Before any integration was built, the team mapped how data was actually moving from Zendesk through to Excel. Where the manual steps were. Where errors were being introduced. What the QA team actually needed the output to look like.
The second was integration design. NDCON designed the Skyvia integration from the ground up: data source configuration, field mapping, transformation logic, and scheduling aligned to the QA team’s reporting cadence. Skyvia was selected as the integration platform because it handled scheduled pulls, field mapping, and data transformation without requiring custom development or ongoing maintenance overhead.
The third was Excel report development. The output was not a generic data dump. Custom Excel workbooks were built specifically for the QA team’s needs: ticket volume tracking, defect categorization, and trend views structured for leadership reporting. Format and structure were treated as deliverables, not afterthoughts.
The fourth was testing and handover. The full pipeline was tested end-to-end, output was validated against manual reports, and documentation and staff training were delivered so the team could operate the system independently.
The Result: Manual Steps Removed, Capacity Returned
The before and after is straightforward.
Before, Zendesk exports were required for every reporting cycle. Data reformatting and cleanup were handled manually by the QA team. Leadership reports were rebuilt each period. There was no consistent audit trail from ticket data to report output.
After, Skyvia pulls data automatically on schedule. Transformation logic runs inside the integration layer. Excel workbooks update without manual intervention. QA managers present accurate data to leadership without rebuilding reports.
The data flow is traceable from Zendesk through to the final output.
The most significant outcome was not the automation itself. It was what the QA team could do with the time they got back. Hours previously spent on exports, cleanup, and reformatting were redirected to actual quality analysis and improvement work.
What This Engagement Demonstrates
Connecting existing platforms with a purpose-built integration layer transforms how teams work. The QA team did not change their tools. They changed how data moved between them.
Raw data from a source system is not the same as reporting-ready data. The transformation logic built into the integration layer is what makes the output useful. That distinction is often overlooked when organizations approach integration work for the first time.
Every manual step removed from a data pipeline is time returned to the people doing the work. That is the operational principle behind every integration engagement NDCON delivers.