Data Quality Dashboards

UX
UI
Strategy
Research

Role:

Objective

The Challenge

In 2020, I participated in a hackathon at Experian, where the goal was to innovate around data management challenges. Our team identified a key pain point for data analysts and business users: visualizing and reporting on data quality. Customers were using various third-party tools to create dashboards, leading to insecure data transfers, higher costs, and fragmented processes.

We aimed to address this by creating a unified dashboard within Aperture Data Studio that would allow users to both analyze data and report on its quality in a seamless, secure environment.

Discovery and Validation

Hackathon Success and Initial Research
Our initial concept was to create a dashboard that served as a starting point for data analysts, but could also be used by business consumers to visualize data quality improvements. After winning the hackathon, we secured funding to develop the idea further.

To validate the need and ensure our design aligned with business requirements, we conducted internal research and interviewed customers from diverse industries. The feedback was clear: businesses needed a secure, integrated way to showcase data quality improvements to their stakeholders, eliminating the need for external tools and reducing the risks of data transfer.

Design and Development

Creating a Modular Dashboard
Building on the customer insights and competitor research, we designed a flexible dashboard that allowed users to:

  • Create Custom Charts: Users could build data visualizations tailored to their specific needs.
  • Modify and Personalize Dashboards: Data analysts could customize their dashboards with drag-and-drop widgets, adjusting layouts to suit their workflow.
  • Share Dashboards with Stakeholders: Business consumers could easily access and view data quality reports, promoting better decision-making across teams.

Our team broke down the vision into small, incremental releases, ensuring that we could deliver value in stages while iterating based on feedback.

Testing and Iteration

Prototyping and User Testing
Our initial prototype, created in Figma, focused on drag-and-drop functionality for dashboard customization. During the first round of testing with five users, we uncovered challenges related to user expectations when adding or modifying widgets. We iterated on the design and conducted a second round of testing with another five users. The improvements were well received, and users found the dashboard more intuitive and flexible.

Throughout the testing process, we collaborated closely with developers to ensure that the final product was both technically feasible and aligned with user needs. Some compromises were necessary, but we ensured that the core functionality remained intact.

Launch and Impact

From Prototype to Customer-Ready Product
We successfully launched the Aperture Data Studio Dashboard in 2021. The product received positive feedback from both internal stakeholders and external customers. By integrating this dashboard into Aperture Data Studio, we provided customers with a centralized solution for visualizing and reporting on data quality, eliminating the need for costly third-party tools.

Key Outcomes:

  • Increased Efficiency: Customers were able to reduce reliance on external tools, streamlining their data management processes and improving security.
  • Positive Feedback: The dashboards were praised for their flexibility and ease of use, contributing to better decision-making for data analysts and business consumers.
  • Ongoing Iteration: Since the initial launch, we’ve continued to iterate and improve the dashboard, incorporating feedback and enhancing the user experience with each release.

Delivering Real Impact

This project not only demonstrated the value of user-centered design but also showed how rapid prototyping and iterative testing can lead to a highly successful product. By building an integrated solution within Aperture Data Studio, we transformed how customers manage and visualize their data, ultimately helping them unlock more value from their data quality initiatives.

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