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karen lai.

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Microsoft Fabric

Case Study

10 minute read

ROLE

Product Design Intern

TIMELINE

2025 (Jan - May)

SKILLS

Product Design

Prototyping

AI UX

Macbook Pro

Macbook Pro

SOME PARTS OF THIS CASE STUDY ARE PASSWORD PROTECTED

If you'd like to read more than what's presented, please reach out to me!

karenhclai@gmail.com

introduction

Microsoft Fabric

A unified data analytics platform that brings together data movement, data engineering, data science, and business intelligence — all in one place

I worked in

these platforms!

I worked in

these platforms!

I worked in

these platforms!

Data Factory

Data Factory

Data Factory

Data Engineering

Data Engineering

Data Engineering

Data Warehouse

Data Warehouse

Data Warehouse

Data Science

Data Science

Data Science

Real-Time

Intelligence

Real-Time

Intelligence

Real-Time

Intelligence

Power BI

Power BI

Power BI

Partner & Industry workloads

Partner & Industry workloads

Partner & Industry workloads

Copilot in Fabric

Copilot in Fabric

Copilot in Fabric

OneLake

OneLake

OneLake

Microsoft Purview

Microsoft Purview

Microsoft Purview

the challenge

Overlapping Features

Fabric has multiple features that do similar tasks for slightly different use cases and users. How can we unify these features and provide one cohesive solution?

AI Ubiquity

How can Fabric implement Al in a ubiquitous way, how can we make it invisible/non- intrusive to the user?

the ask

OVERLAPPING

FEATURES

How can we unify these features features that do similar tasks in Fabric and provide one cohesive solution?

AI UBIQUITY

How can we implement Al in a ubiquitous way, how can we make it invisible/non- intrusive to the user?

GENERAL RECOMMENDATIONS

How can we change the ui/ux experiences for user pain points?

How might we simplify Fabric’s onboarding and AI flows to help users navigate complex data systems with clarity?

DISCOVER

Research

DESIGN

Reflect

research

Information Architecture

outlining user flows and feature journeys across Fabric's workloads

powerbi

warehouse

science

engineering

factory

real time intelligence

research

Main Insights

What did we take away from the Information Architecture map and user journey?

DISCOVER

Research

DESIGN

Reflect

Fragmented workloads

The 6 workloads function well individually, but feel disconnected.

Overlapping features

We found that the challenge isn't complexity itself but inconsistent structure and terminology.

Data Engineering

Data Factory

complex users, unclear flows

Fabric’s users are technically skilled

Lack of clarity (not data depth!) causes onboarding friction and feature drop-offs.

research

User Interview Demographics

job roles

data field

Senior Data Engineer

Analytics Engineer

Data Engineer

FIEld Solutions

Field Engineer

Lead Solutions Architect

non Technical

Business Analyst

Contractor

Founder

by the numbers

where I sourced interviews and and how many I completed

experience

users’ experience with Fabric and/or PowerBI

16

interviews

< 2 years of experience

< 2 years of experience

5+ years of experience

5+ years of experience

2-5 years of experience

2-5 years of experience

DISCOVER

Research

DESIGN

Reflect

RESEARCH

User Interviews

Framework to gauge user pain points and insights.

feature experiences

feature experiences

value satisfaction

value satisfaction

AI ubiquity

AI ubiquity

general experiences

general experiences

competitive landscape

competitive landscape

01

AI Feature Uncertainty

Users were unaware of how AI was embedded in the platform and unaware of AI features.

02

Task Completion

Users struggled to complete certain tasks due to their uncertainty about what steps to take next or where to find necessary information.

03

Onboarding

Unintuitive navigation of tools/workspaces, leading to reduced productivity and frustration.

DISCOVER

Research

DESIGN

Reflect

Design

Microsoft Fabric Design System

To maintain a consistent interface and visual design across all iterations

DISCOVER

Research

DESIGN

Reflect

microsoft Fabric Case Study

The rest of the case study is password protected.

If you'd like to read more than what's presented, please reach out to me!

go to case study

Reflection

Over the course of 5 months, I worked with Microsoft Fabric’s design team to explore and improve how users interact with complex data tools at scale. My role spanned from early research synthesis to prototyping and design iteration, working closely with designers, PMs, and engineers.

Big thanks to the Microsoft Fabric team, especially Gresshaa Mehta and Brent Sandifer for their guidance, collaboration, and trust throughout this project!

WHAT I'VE LEARNED

Designing for Scale Requires Systems Thinking

Working within a product ecosystem as large as Microsoft Fabric taught me to think beyond individual screens. Every design decision had to align with broader product principles, accessibility standards, and cross-platform consistency.

Cross-Functional Collaboration is a Design Skill

I learned how to navigate feedback loops between designers, PMs, and engineers—balancing technical constraints with user needs while keeping the end-to-end experience cohesive.

The Power of Storytelling

Clear, engaging narratives made it easier to communicate my ideas and influence decisions in team reviews. I saw firsthand how framing a problem and solution can turn a good design into a well-supported one.

BIGGEST TAKEAWAY


Great design goes beyond visuals or features — it’s about understanding the people who use it. Throughout this project, I learned that investing in empathy and building trust with users transforms solutions from functional tools into meaningful experiences.

Thanks for reading!