Expert help when you are stuck, or when you need advice or guidance
Technical support is a must-have for the successful implementation and running of Power BI reporting services. Errors and broken code are a common occurrence on Power BI projects.
Power BI is a powerful but complex ecosystem — and it keeps growing. Even experienced practitioners, and even after investing in Power BI training, regularly encounter situations where progress stalls completely.
The cost of being stuck is not just the hours spent searching for answers. It is delayed reports, team members waiting on outputs, pressure from management, and the risk of building a solution on a flawed foundation that creates bigger problems down the line. In our experience, figuring things out alone is expensive — in time, productivity, and sometimes in the quality of what gets built.
Power BI projects fail or stall for a range of reasons. Based on our implementation experience and the patterns we see repeatedly, the most common challenges include:
Calculations producing wrong results, unexpected blanks, or context errors that are difficult to diagnose without a strong grasp of filter context and data model relationships.
Scheduled or manual refreshes failing — often caused by file or folder changes, renamed columns, expired credentials, privacy level mismatches, or broken table relationships in the data model.
Reports that work but are built on a poor data model — overly complex measures, incorrect relationships, or a structure that cannot scale. This often only becomes apparent when the solution needs to be extended or handed over.
Data transformation steps breaking when source data changes — column names, data types, file structures, or connection issues that cascade into report failures.
BI projects taking much longer than expected, failing to deliver measurable value, or not gaining user adoption — common when the problem statement is unclear, scoping is rushed, or users are not engaged early enough.
Slow reports, long refresh times, or visuals that lag — often a symptom of an inefficient data model, unoptimised DAX, or large data volumes being handled without appropriate architecture.
Getting Power BI to reliably connect to and refresh from your actual data sources is often harder than it looks. Common challenges include:
Many BI projects fail not because of a technical problem, but because of a communication one. Business teams know what they need but cannot articulate it in technical terms. IT and BI teams can build what they are asked for — but do not always understand what the business actually needs or how the numbers work.
The result is a solution that is technically correct but practically useless — reports that do not match the source numbers, dashboards that answer the wrong questions, and a team that does not trust or use the output.
A growing area of complexity is connecting Power BI to AI tools and Model Context Protocol (MCP) servers — enabling AI assistants to interact directly with your data models and reports.
Our principal consultant has worked hands-on with the Microsoft Power BI MCP server and AI integrations — including the glitches and troubleshooting that comes with being at the frontier of this technology.
If you are exploring Copilot, agentic AI, or MCP-based workflows with Power BI, we can help you navigate the setup, troubleshoot connection issues, and apply these capabilities in a way that delivers real value.
Our technical support is practical and hands-on, drawing on years of Power BI consulting and implementation across many sectors. Our background combines finance and technology — a CA(SA) with CFO experience — with strength across the public and private sectors. Use us however suits your team:
Ad-hoc help on a specific problem — a broken DAX measure, a failing refresh, a Power Query error. What can take your team days to unravel, experienced eyes often resolve quickly.
A review of your build before you go too far — data model, report structure, and DAX — with honest feedback on whether it will scale, hand over, and be trusted. We share the reasoning, so your team learns as we go.
Before users see it, your Power BI numbers must match your existing reports. We reconcile your outputs, resolve every discrepancy, and make sure the report is trusted from day one.
A Power BI expert on call who also speaks the language of business — translating between business and IT, turning requirements into specs and explaining outputs back in plain terms, so projects don't stall on miscommunication.
AI tools like ChatGPT and Claude are genuinely useful for Power BI troubleshooting — and we use them ourselves. But as our own experience confirms, there are problems that even the best AI tools cannot solve on their own. The nuance of a specific data model, the context of a specific reporting requirement, or a stubborn refresh error with multiple contributing factors often requires human experience and judgement to resolve. AI accelerates the process — it does not replace deep expertise.
These articles share real experiences and practical insights on navigating the challenges that come with Power BI projects:
Implementation Guide
The ten steps that make a Power BI implementation succeed — from reconciliation to ownership — so your project lands faster and keeps delivering.
More →Project Planning
How long a Power BI implementation really takes, the phases involved, and what speeds it up or slows it down.
More →BI Project Success
Why BI projects stall, fail to deliver ROI, or run over time — and the practical steps that separate successful implementations from expensive disappointments.
More →