Self-service business intelligence is an approach in which business users build their own reports, dashboards and data models instead of relying on a central BI team; without governance it can lead to duplicated content and rising costs.
Most Power BI environments start fast and stall under copy-paste sprawl: duplicated PBIX files, conflicting measures, and “spreadmart” dashboards that nobody fully trusts. The fix isn’t another naming convention—it’s a model-first architecture. Microsoft…
In this episode, we break down Microsoft Power BI’s pricing structure to help you understand the different license options, costs, and features available across the Power BI ecosystem. Whether you're comparing Power BI Free, Pro, Premium Per User, or Premium…
Finance teams have ERP data, Power BI reports, Excel everywhere and now AI agents, yet agents do not automatically understand what revenue or margin means in their business. This conversation with Rishi Sapra is for data, BI and finance leaders who want…
Timeline of episodes about Self-service BI
Articles about Self-service BI (2)
Uncovering the Hidden Costs of Self-Service BI · Mirko Peters Welcome back to the podcast and our companion blog! If you are like most modern business leaders, you have likely heard the pitch for self-service business intellig…
Understanding Fabric Semantic Models · Mirko Peters If you’ve ever tried to make sense of your company’s data, you know how complicated it gets real quick. That’s where Fabric semantic models come i…
How can organizations control self-service BI costs?
Understand the licensing models, train users to avoid misinterpreting data, prioritize clean and consistent data and implement strong governance. These steps prevent hidden costs and loss of trust in analytics. · From the episode: Choose the Right Power BI License and Capacity
How might self-service BI change with agents?
Agents could build and operate parts of the architecture while humans supply business context. Self-service BI would then shift from users building their own reports to people defining what the data means, with the agents handling more of the technical work. · From the episode: From Financial Data to AI-Ready Decisions
Short info above, community knowledge below: add practical tips, examples or corrections. New contributions are reviewed first; trusted members publish directly.
Experts and companies for this topic
Nobody has listed this topic yet. Add it to your profile.