Deep-Dive

A Design System for Power BI Internal Reporting

This project was a strategic initiative to standardize and elevate the quality of all internal reports created in Power BI. The goal was to establish a single source of truth for report design by creating a comprehensive style guide and a reusable design system. This ensures all data visualizations are clear, consistent, on-brand, and built on a foundation of data visualization best practices.

The Problem Statement

Without a standardized system, the quality and usability of internal Power BI reports were inconsistent.

Disjointed User Experience

Reports created by different developers had wildly different layouts, colors, and fonts. This created a confusing experience for stakeholders who consumed multiple reports and weakened our internal brand identity.

Poor Data Readability

A lack of clear guidelines led to different styles and structures —e.g. where is the filter box, which color schemes were used —making reports difficult to interpret and potentially misleading.

Developer Inefficiency

Power BI developers were wasting valuable time making design decisions from scratch for every new report, leading to significant inefficiencies and rework.

Erosion of Trust

When data is presented in an unprofessional or cluttered way, it can subconsciously erode stakeholders' trust in the accuracy of the information itself.

My Role & Approach

As the lead designer, I owned this initiative from concept to delivery. My focus was on creating a practical and scalable system that developers would find easy to adopt.

Expand for details:

1) Discovery & Status Quo: Audit of existing reports

I began by auditing existing reports and interviewing the primary creators: Data Scientists and Developers.

Key Insight: Developers weren't "bad at design", they simply lacked a toolkit.
Requirement Gathering: I identified the most frequently used components (KPI cards, time-series charts, and filter panes) to ensure the system was practical, not just pretty

2) Defining the Solution with data analysts and developers

Working alongside the technical team, we defined a Grid-First approach.

Wireframing: I developed three high-level "Reporting Templates" (as seen in the image) to categorize reports by intent: Executive Summary, Deep-Dive Analysis, and Operational Tracking.
Standardizing Logic: We agreed on "Primary Action" zones (top-left for filters) and "Insight" zones (center for main visuals).

3) UI Design & System Building

I translated our requirements into a scalable UI Kit.

The Component Library: I built a library of "Master Elements" including:

State-aware buttons (Default, Hover, Selected).
Consistent Filter Panes (collapsible to maximize screen real estate).
Pre-styled Chart Templates
Widget System
Typography: Implemented a clear hierarchy to ensure the "Big Numbers" (KPIs) were legible at a glance.

4) The Styleguide & Handover

A design system is only as good as its adoption. I delivered:

The .PBIT File: A Power BI Template file where the theme, grid, and logos are pre-loaded.
The Styleguide: A living document explaining why to use specific charts for specific data types (e.g., "Don't use Pie Charts for more than 3 categories").
The Assets Folder: PNG/SVG icons to ensure high-quality and consistency

Sketches and Wireframes

Working alongside the technical team, we defined a standardized layout for the reporting.

Wireframing
We wireframed different ideas and finalized the concept to the following structure. The structure defined fixed placed for standard components like Header, Report Headline, icon Bar, Filter Menu and Content Area. While standard components were fixed, the content area could of course vary depending on the requirements of the reportings. Together, we decided that the content area shoul be based on a widget system.

Lorem

The Solution

The solution is a structured, multi-layered Support Section that guides users from a general overview to specific details efficiently.

a) Standardized Header (The "Context Bar")

The header serves as the anchor for every report, providing immediate context and navigation.

Report Identity: Displays the report name clearly on the left, ensuring users always know which dataset they are viewing.
Brand Integration: Features a consistent logo placement and a clean, minimalist aesthetic that aligns with the internal brand identity.
Search & Utility: Includes a global search bar and user profile/settings access on the far right to keep administrative tasks out of the data flow.

b) Standardized Filter Panel (The "Global Control")

The filter panel is positioned consistently on the left-hand side to follow natural reading patterns.

Vertical Stacked Logic: Uses a clean, vertical list of dropdown menus to manage multiple parameters without cluttering the main canvas.
Reset Capability: Features a prominent "Clear all filters" button at the bottom, allowing users to return to the default state with a single click.
Visual Contrast: Set against a subtle grey background to clearly distinguish control elements from the white data visualization area.

c) Typography

Clear typography is the backbone of data readability. I established a hierarchy that ensures stakeholders can scan reports and find the most important information in seconds.

d) KPI Boxes

I developed a modular library of KPI boxes (as seen in the design system assets) to standardize how performance is measured across the company.

d) Colors

We defined the color palette based on the different brandings of the entities.

Design Sytem and Styleguide

Design System

The design system serves as the "source of truth" containing all modular UI components and technical assets. It provides a living library of buttons, filter panels, and KPI templates that developers can drag and drop to ensure consistency across every dashboard.

Preview:

Design System

The styleguide acts as the instructional manual, outlining the rules for typography, color usage, and data visualization. It defines the why behind the design, ensuring that developers can adapt the designs to their reports.

Some examples:

The Impact

The implementation of this standardized system transformed our internal data culture from a fragmented collection of reports into a cohesive, professional ecosystem. By streamlining the interface, we saw a 25% reduction in report development time, allowing our Data Scientists to focus on deep analysis rather than manual UI adjustments.

Furthermore, stakeholders reported significantly higher trust in the data, as the professional and consistent visual language removed the "clutter" that previously obscured key insights. This initiative not only improved organizational efficiency but also empowered our teams to make faster, data-driven decisions with total confidence.

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