Empowering data teams with AI-powered automation

A leading European data provider was facing significant operational bottlenecks. The subject matter experts for data collection, cleansing, and processing were heavily reliant on manual workflows and Excel-based processes. Whenever teams needed customized solutions or automation, they had to submit requests to the central IT department—which led to delays and limited innovation at the team level.

Objective

Our goal was to empower data experts to create their own automated workflows without relying on the central IT department. This would reduce repetitive manual tasks, improve data quality, and increase operational agility.

The customer had already licensed and implemented Microsoft Copilot, but without achieving the desired effects.

Analysis and identification

Together with the data teams, we analyzed existing processes and identified effective automation opportunities. The focus was on use cases that were time-consuming and had potential for repetition, particularly in data collection and cleansing.

Training and empowerment

In a workshop, we taught data specialists the basics of using Copilot and Copilot Studio. The training was tailored to the specific daily challenges faced by the teams to ensure immediate applicability.

In particular, we worked together to identify the limitations of Copilot in terms of quality and scalability, the basic tools Copilot Studio offers to overcome these limitations, and how performance can be further enhanced by integrating Azure AI.

Use case analysis

In another workshop, we applied these fundamentals and knowledge to the customer's specific use cases, created sample Copilot Studio flows, and also explained testability and debugging in such workflows.

For many of the use cases, we were able to approach a working solution directly in the live workshop.

Result

The transformation enables fundamental changes in the client's daily work life.

Increased autonomy

Data teams create and iterate their own automation solutions without IT wait times.

Improved data quality

Automated validation reduces human error and increases consistency.

Increased job satisfaction

Specialists focus on analytical work instead of repetitive tasks.

Scalable foundation

The citizen developer model creates a multiplier effect for the entire organization.

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