Data Catalog
My role
UX/UI designer
and researcher
Team
UX/UI lead
UX/UI designer
Product manager
Status
Accepted Q4 2023
PROJECT OVERVIEW
The Data Catalog empowers General Motor’s employees to explore a centralized internal repository housing both on-premises and cloud data. Its primary aim is to streamline the search and discovery process by providing our users with the comprehensive information required to easily navigate General Motor's data. Here, users can uncover new data pertinent to their roles and efficiently assess their access permissions, while also facilitating prompt requests for additional data access.
01/
Launching the research phase with strong momentum.
understanding
Our team began creating this product from the ground up so it was our goal to understand who our our current and future users are, their problems, needs and communicate a solution to our stakeholders.
Through our research, we discovered that our existing users actively utilize Maxis Workspaces (an internal product developed by our UX team), Databricks, and Azure. Then, I conducted user interviews to understand the needs, and pain points they were facing with their current products. This would provide us with insights into potential areas for improvement in the new product.
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02/
What problem do we need to solve?
defining
Leveraging insights obtained from our initial round of user interviews, we initiated the roadmap planning phase. This encompassed brainstorming for the vision, outlining problems and opportunities, and exploring potential solutions.
Problems & Opportunities
- What problems do our users face today?
- What opportunities do we have today that will help us achieve our vision?
03/
Our expectations from the data catalog...
Recognizing the need for alignment, I organized a series of workshops with senior leadership and other stakeholders to maintain focus and drive progress. This collaborative effort ultimately led to the clear definition of the desired features, as detailed below:
features
Request Data Access
Facilitate seamless discovery and access of cloud and on-premises data, including easy request functionalities, where users can locate internal data effortlessly.
Organized Data Architecture
Provide users documentation on available datasets, including their descriptions, lineage, and usage instructions, along with heuristics and structure to determine the optimal data.
Enhanced Search Capabilities
Enhance search capabilities with user-friendly features like displaying product owners and data lineage, while also emphasizing clear metadata, data previews, and team affiliations to highlight popular and high-quality content.
04/
Establishing personas
users
After conducting multiple interview rounds, we distilled themes from each. This thorough three-phase process not only sharpened our insights but also equipped us with a profound understanding of the three unique user personas who would actively participate in our platform.
05/
Before & after
designs
As our criteria evolved over time, our designs adapted to meet the updated requirements, ensuring alignment with the latest specifications and user expectations.
We used the "crazy 8’s" method to sketch out ideas for the homepage, search results, and data page separately. We spent time creating different options for each page and then voted on our favorite parts. After choosing the best elements, we combined them into new pages and showed them to our manager and product manager for approval.
05/
Several iterations later...
final designs
With the approval of the designs, we proceeded to refine the final versions.
CloudServe seamlessly complemented our recently developed data catalog, so we leveraged the existing design system with some modifications to infuse a distinctive touch into this product.
Screen: Homepage
Screen: Data Page
06/
How'd we do?
impact
The data catalog successfully fulfilled its primary objective of enabling users to request access to both on-premises and cloud data. Through meticulous data architecture organization, information became readily discoverable, and we significantly bolstered search functionalities, elevating the overall user experience.
Optimized Resource Utilization
This data catalog for on-premises and cloud data led to a notable 12% decrease in resource allocation expenses. This substantial cost-saving initiative stemmed from the streamlining of data access and management procedures, efficient resource utilization, and enhanced data governance practices across the organization.
Integrating With cloudServe
As we're developing a self-service cloud infrastructure provisioning product, our upcoming focus is to leverage insights from our data catalog project. This will guide the design team in effectively integrating both products.
Next Project
cloudServe
