Reflections on the Fabric Analyst in a Day Workshop: A Day of Data Revelations

 A Look Back at the Microsoft Fabric Analyst in a Day Workshop: Orlando, Florida (May 4, 2026) 

Last month in Orlando, a group of data professionals spent a full day with our team to learn how Microsoft Fabric turns raw data into actionable insights. We were taken aback by the enthusiasm, and we had so much great feedback from the attendees.

A recurring theme throughout the event was how successful AI initiatives begin with a strong data foundation. Many of the attendees came into the event with their sights set on an eventual Copilot rollout (or at least some expansion of their AI initiatives). Judging by the attendees’ responsiveness, they clearly saw potential in Fabric for achieving their goals.

All that to say, we felt that having this workshop in person was a huge advantage for all involved. People can learn information from a general presentation, sure, but there’s really nothing like having a chance at intensive, hands-on learning.

That’s part of why we continue to run these workshops alongside Microsoft. We’ve spent more than a decade as an official Microsoft Partner, including partner designations for Data and AI, Modern Work, and Digital/App Innovation (Azure). We’ve seen the impact of these tools for businesses for a while now, but the era of AI has only risen the value of Fabric training.

From the start, conversations centered around issues like slow reporting cycles and disconnected data sources. After a full day working through the platform together, attendees could see how to connect their data, structure it properly, and build outputs they could trust.

Morning Session: Establishing a Single Source of Truth

We started the workshop with a familiar scenario: data was spread across SharePoint, SQL databases, and cloud storage. The first step was bringing that data together using OneLake.

Attendees connected multiple data sources using Data Factory pipelines and shortcuts. This allowed them to access data where it already lived without duplicating it. That alone cut complexity and improved governance.

Next, we built a Lakehouse to serve as a shared foundation. This became the central layer for both data engineering and analytics work.

During the data preparation phase, attendees used Data Wrangler to clean and transform their datasets. The visual interface made it easy to standardize and reuse transformation steps. Tasks that often require manual effort or scripting were completed quickly and in a way that can be repeated month after month.

We also incorporated Copilot throughout this process. It helped generate DAX measures, suggest transformation logic, and assist with report creation. Attendees were able to review and adjust everything, which reinforced understanding while improving speed.

By the end of the morning session, every participant had a connected and structured data foundation that could support broader team use.

Afternoon Session: Turning Data into Scalable Assets

The afternoon focused on building on that foundation to create reliable, high-performance outputs.

Attendees developed semantic models within the Lakehouse and used Direct Lake in Power BI to work with large datasets without performance delays. Reports responded quickly, even as data volumes increased.

A key focus during this session was continuity across the workflow. Data pipelines, transformations, models, and reports all operated within the same environment. This reduced rework and made it easier to maintain consistency across reporting cycles.

What Attendees Walked Away With

By the end of the workshop, each attendee had built a complete, working solution:

• Connected data sources across multiple environments
• Automated pipelines for ingestion and transformation
• A structured Lakehouse and semantic model
• Fully functional Power BI reports
• A path to a data foundation that powers AI initiatives

From a facilitator’s perspective, that outcome matters the most. The goal is to provide attendees with something practical they can use immediately, whether they are improving reporting processes or scaling analytics across their organization.

Final Takeaway

Consistently, one takeaway comes through in every session. Many organizations face challenges with their data foundation, which then impacts reporting and decision-making.

Microsoft Fabric brings these components together in a single environment. When attendees work through the process hands-on, the benefits become clear quickly.

For any teams interested in their own Fabric workshop or taking the next step with their data foundation, we welcome a conversation with you. Reach out and let us know.