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Elevating Dashboard Experience | Company: Informatica | Year: 2022

How I Cut Support Tickets by 78% by Visualizing Data Lineage

Audience

Data Stewards

Business Users

Data Owners

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Team

2 Designers

3 Developers

2 Product Managers​

My Role

UX Designer

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Impact at a Glance

  • Data Lineage investigation time dropped from hours to minutes.

  • 78% reduction in data lineage-related support tickets.

  • 25% improvement in customer retention for MDM product.

  • 85% feature adoption rate within first 3 months.

User Testimonial

"Finally, I can tell the story of my data. This has transformed how we handle data governance. What used to take me half a day now takes 10 minutes." - Senior Data Steward, Fortune 500 Financial Services

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Fig 1: High Level Overview Screen Showing Data Performance

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Fig 2: Comparison View on How the Golden Data is Created

The Challenge: Lost in the Data Maze

Imagine being a data steward responsible for ensuring data quality across your organization, but having no visibility into how your golden master records were actually created. This was the reality for Informatica's Master Data Management (MDM) users.

The Core Problem

The previous MDM Source Record feature was a black box—users couldn’t see which source records contributed to the golden record, how data flowed or transformed, what source performed best, or why and how conflicts were resolved.

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Fig 3: Comparison View: Old Screen

The Business Pain

60% of User Support Tickets

Related to data lineage confusion

Data Stewards Spent 40%  of Time

Manually investigate record sources

Customer Satisfaction Scores

Were very low due to usability issues

Demo Conversion Rates Dropped 25%

Due to competitive disadvantage

Understanding Our Users

Data Stewards (65% of users) need detailed lineage and conflict resolution tools to ensure data quality and compliance, enabling them to make informed decisions about data accuracy. Business Users (25%) seek high-level, non-technical insights to understand inconsistencies in reports and quickly assess overall data health. Data Owners (10%) require visibility into source system performance, alerts for missing contributions, and an understanding of data flow patterns to maintain system reliability.

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Research Methodology

  • 12 stakeholder interviews (internal and external)

  • Competitive analysis of 5 industry leaders

  • Usage data analysis from 2,000+ active users

  • Support ticket analysis of 500+ recent cases

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"Make it easy for the approver -  provide the context for the changes..."

"We need to tell the Business User in a very simple way what is happening and why…."

" Give me an end-to-end story on how a master record is created..."

"Help me easily figure out why my numbers don’t add up..."

The Solution Strategy

We reimagined the Source Record experience around the principle of "visual storytelling", making data lineage as clear as following a timeline.

Progressive Disclosure

Show overview first, details on demand

Contextual Actions

Provide relevant actions based on user intent

Visual Hierarchy

Use design to guide users through complex information

Performance Transparency

Make system performance visible and actionable

Fig 4: Key Design Principles Used

Feature Deep Dive

Interactive Data Lineage Visualization addressed the lack of visibility into how master records were built over time. The solution introduced a chronological, interactive timeline that clearly mapped each source contribution, highlighted data transformations and merge conflicts, and displayed quality scores at every step. Users could click into specific nodes to investigate details, making lineage both transparent and actionable.

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Impact: Reduced investigation time from hours to minutes.

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Fig 5: Ancestry Detail

Contextual Exploration Panels solved the problem of fragmented navigation, where users had to switch screens and lose context to access specific details. The solution introduced in-place panels that allowed users to drill into any source record without losing their place, compare competing values side-by-side, view match rules and confidence scores, and access historical changes directly within the workflow.

 

Impact: This led to a 75% reduction in navigation steps required to access critical information.

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Fig 6: Smart Drill-Down Experience

Customizable Comparison Views addressed the rigidity of the previous system, which offered a one-size-fits-all layout despite varying user needs. The new solution enabled users to create flexible layouts by grouping attributes based on relevance, saving personalized views, filtering by source, date range, or quality metrics, and exporting specific comparisons for reporting.

 

Impact: 90% of users created and consistently used custom views, enhancing both efficiency and relevance in data analysis.

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Proactive Source Monitoring solved the issue of users identifying missing or problematic sources only after data quality issues became apparent. The solution introduced real-time visual indicators and alerts for non-contributing expected sources, unusual contribution patterns, degrading quality scores, and source system outages impacting data flow.

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Comparison View

Key Learnings & Next Steps

What Worked Well

  • User-centered approach: Involving users throughout the process led to solutions that truly addressed their pain points

  • Visual storytelling: Complex technical concepts became accessible through thoughtful information design

  • Iterative testing: Regular feedback loops prevented major redesigns late in the process

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Challenges Overcome

  • Technical constraints: Worked closely with engineering to find creative solutions within system limitations

  • Stakeholder alignment: Balanced competing priorities through data-driven decision making

  • Change management: Created comprehensive training materials to ensure smooth adoption

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Future Opportunities

  • AI-powered insights: Integrate machine learning to predict data quality issues

  • Real-time collaboration: Add features for team-based data governance workflows

Personal Growth

This project pushed me to become a better strategic designer. I learned to:

  • Think systematically about complex enterprise software challenges

  • Communicate design value in business terms to executive stakeholders

  • Balance user needs with technical feasibility and business constraints

  • Lead cross-functional teams through ambiguous problem spaces

 

The success of this redesign has become a template for how we approach other complex enterprise UX challenges at Informatica, emphasizing the power of making complex systems feel intuitive and human-centered.
 

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