Scaling Self-Service BI in Power BI: A Webinar Recap 

Self-service Business Intelligence (BI) promises to empower every team member with the data they need to make smarter decisions, faster. 

But how do you give users the freedom to explore data without creating a chaotic environment of inconsistent metrics and untrusted reports? It’s a delicate balance between empowerment and control. 

In the most recent Zebra BI webinar, our experts Tilen Barbarič and Mark Leskovšek detailed a proven framework for building a scalable self-service BI environment in Power BI. 

They shared practical strategies to ensure every report remains governed, consistent, and ready for decision-making. This recap expands on their key insights, offering a detailed guide to balancing user freedom with robust data governance. 

Understanding self-service BI 

At its core, self-service BI is an approach that enables all business users (not just data specialists) to access, explore, visualize, and analyze information independently. 

The goal is to equip people across the organization to answer their own data questions using governed, user-friendly tools. When implemented correctly, business users get timely insights, while BI teams can shift their focus from fulfilling ad-hoc requests to strategic governance and system optimization. 

As a general rule, there are two different tiers of self-service users: 

• Tier 1: End users who consume reports with basic interactions (cross-filtering, bookmarks) 

• Tier 2: Users with more advanced needs requiring greater flexibility and customization 

The core challenge: governance vs. freedom 

The biggest hurdle in self-service BI isn't the technology itself; it's finding the right balance between control and autonomy. 

You want to empower users to find their own answers, but you also need to ensure the data they are using is accurate, secure, and consistent. 

Without proper governance, you risk a free-for-all where metrics like "revenue" or "margin" mean different things across different departments, leading to confusion and poor decisions. 

Here are some additional key challenges and statistics brought up by Tilen and Mark during the webinar: 

• Market growth: Self-service BI market growing ~19% annually 

• Success rate: Only ~1/3 of companies report successful implementations 

• Main obstacle: For most organizations, the main obstacle to implementing self-service BI is governance, not technology 

• Semantic layers: According to a BARK survey, 73% of companies identify a lack of a consistent semantic layer and metric definitions as the top barrier to scaling self-service BI. 

Core building blocks for self-service reporting 

Every scalable self-service environment should master these foundational elements to enable users to explore data independently while maintaining governance and trust. 

Proper data modeling 

A well-structured data model using star schema is the foundation of any successful self-service BI implementation. 

This approach organizes information into fact tables connected to dimension tables, including a calendar table for time intelligence, keeping data clean, efficient, and easy to maintain while enabling scaling across the organization. 

Disconnected tables 

Disconnected tables are dimension tables without defined relationships to your fact table, enabling dynamic filtering and calculation switching. 

Common examples include KPI tables (Revenue, Cost, Gross Profit), period calculation tables (MTD, YTD, Last 12 Months), and comparison type tables (vs. Previous Year, vs. Plan). Create them by going to Home > Enter Data, then combine them with switch statements for flexible user selections. 

Field parameters 

Field parameters allow users to dynamically select which dimensions they want to analyze—region, country, division, product group, or salesperson—switching perspectives with a single click. 

They support custom hierarchies and multi-level selections (like Region + Country simultaneously), providing more freedom than predefined views while maintaining control over available options. 

Switch statements 

Switch statements enable dynamic calculations that respond to user selections from disconnected tables. A single "AC Value" measure can calculate Month-to-Date, Year-to-Date, or Last 12 Months based on user selection, eliminating multiple separate measures and making reports more maintainable with less measure sprawl. 

Bookmarks 

Bookmarks capture and save specific report states—filters, layouts, visual types, and visibility settings—for instant recall. 

They're powerful for creating predefined views for common analysis scenarios, like switching between table and chart views or toggling hierarchy configurations. Be cautious not to overuse them as maintenance complexity increases significantly. 

Report page tooltips 

Tooltips provide additional context and insights by hovering over data points, showing detailed breakdowns or trend analyses without leaving the current view. 

They're intuitive for non-technical users and efficient—queries only trigger on hover, not during initial page load. You can even combine them with bookmarks to create dynamic tooltips that change based on slicer selections. 

Want to see all this live in action? Watch the full webinar and see how Tilen and Mark tackled a quick sales & profitability analysis and financial statements, using advanced techniques like: 

• Dynamic KPI selection (Revenue, Cost, Gross Profit, Margin) 

• Period calculations with slicers 

• Field parameters for flexible dimension analysis 

• Rolling periods for trend analysis (last 30 months, 2 years, 3 years) 

• Small multiples for comparing multiple categories 

• Combo charts for multi-metric analysis 

• Single report switching between Income Statement, Balance Sheet, and Cash Flow 

• Account hierarchies with proper categorization 

• Waterfall charts showing profit composition 

• Dynamic comparison scenarios (vs. Plan, vs. PY, vs. Previous Month) 

• Dynamic titles and column headers 

Zebra BI Visual Benefits 

As showcased by Mark and Tilen, Zebra BI visuals enhance Power BI's native capabilities with features specifically designed to accelerate self-service reporting while maintaining governance and consistency. 

• Automatic variance calculations eliminate the need to create separate measures for comparing actuals versus plan or previous periods—simply drop in your comparison values and the visual instantly calculates and displays variances, saving development time and reducing measure sprawl. 

• Standardized design ensures every visual across all reports follows the same formatting and layout conventions, providing governance through consistency so users can trust they're looking at data the same way regardless of which dashboard they're using. 

• Interactive features like switchable chart types, CAGR arrows, annotations, and commentary enable users to personalize their analysis and add storytelling elements directly within visuals without requiring additional coding or overlaying separate objects. 

• Flexible displays support multiple visualization types including tables, charts, waterfalls, and combo charts within the same visual object, allowing users to switch between structural analysis and trend analysis with a single click to get the view that best answers their question. 

• Built-in governance through consistent formatting means developers can speed up report creation while ensuring professional, standardized outputs that immediately help users spot key insights through proper visual design. 

• Interaction controls let developers decide exactly how much freedom to give different user groups—completely locking down visuals for managed tier-one experiences or enabling full customization options for more advanced users, all within the same visual type. 

Lessons from KPN's success 

The webinar highlighted the success story of KPN, a leading telecommunications company. They successfully implemented a self-service model by creating "exploratory dashboards" with Zebra BI. 

Their BI team designed a robust, governed reporting space, but gave users powerful, interactive tools to explore the data on their own terms. 

Want to learn more about KPN's success story? Read more about it here. 

A quick overview and key takeaways 

Empowering users through self-service BI is an ongoing process that requires careful planning, support, and adaptability. By fostering a data-driven culture and continuously improving your BI solutions, you can ensure long-term success and value for your organization. 

Remember: 

1. Balance is critical: Find the right mix of governance and freedom 

2. User engagement is essential: Talk to end users regularly for feedback 

3. Start simple, scale gradually: Build foundational reports, then add flexibility 

4. Performance matters: Optimize data models before adding complex calculations 

5. Context is king: Provide variance, comparisons, and trends to support decision-making