Low Code Solutions for Engineers
Software developers frequently spend hours writing or parsing extensive JSON to connect dashboards to the right data sets—especially when different APIs and authorization schemes come into play. I designed a user-friendly yet technically robust feature to help software developers and back-end engineers quickly integrate dashboards with external data sources, all within a low-code environment.
Problem Space
Software developers frequently spend hours writing or parsing extensive JSON to connect dashboards to the right data sets—especially when different APIs and authorization schemes come into play. Even experienced back-end engineers find this time-consuming.
Key Challenges
Complex Setup
Setting up API requests and JSON parsing demanded a deep knowledge of back-end development.
Varied Authorization Flows
Different projects required different auth methods (e.g., token-based, Honeywell's internal roles, custom headers).
Undefined Low-Code Interface
We needed a new UI paradigm to accommodate advanced developer needs while still being approachable for non-technical users.
Approach
Developer-Centric Research
Whiteboard Workshops: Held multiple sessions with engineers from various disciplines (back-end, DevOps, integration specialists) to map out how they currently set up data connectors.
Storyboarding: Walked through hypothetical user journeys step by step, from discovering an API endpoint to seeing the data appear on a dashboard tile.
Collaborative UI Sketching
Co-created low-fidelity sketches with developers, focusing on how to translate typical code-based tasks (e.g., JSON queries, authorization tokens) into a guided interface.
Mental Model Alignment: Ensured the UI mirrored how developers think—i.e., specifying API requests, setting headers, and retrieving JSON responses.
Early Validation: Gathered feedback immediately after each sketching session to confirm that we were reducing rather than adding complexity.
Competitive & Comparative Analysis
Examined existing data connector features in tools like Kafka, Azure, Power BI, and Grow.
Printed out key screens and workflows, then reviewed them with our developers to understand technology underpinnings (e.g., how other tools handle query building, error handling, or version control).
Features
Data Connector Setup
API Entry & Naming: Users can enter an API URL, select a connector type (RESTful, time series, or HTTP), and name the connector. The naming convention is critical so users can quickly recognize which connector to reference later.
Tile Configuration Integration
Connector Availability: Once saved, the data connector appears in the tile configuration interface for rapid selection.
Low-Code Emphasis: More technical tasks (like writing SQL queries) are still available for those who need them, but simpler connections can be made by non-technical users using guided wizards and pre-set options.
Parameters & Authorization
Key-Value Pairs: Developers specify the query parameters or SQL commands as "key-value" entries. To simplify writing complex queries, the interface provides a "Show Query Builder" toggle, letting users visualize or edit their queries in a friendlier format.
Scalability & Maintenance
As new data sources or APIs emerge, developers can add new connectors without re-engineering the entire dashboard.
The design framework encourages reusability—connectors can be shared, cloned, or modified for different teams and clients.
Data Fetch & JSON Parsing
Request & Response: Upon making the request, the tool returns a JSON blob. Users navigate through that JSON structure to identify the "path to data"—the specific subset they want to display.
Visibility into JSON: The UI includes a simple code viewer, so users can quickly locate the relevant objects and arrays.
Mockups
While parts of the process remain highly technical, early metrics indicated a 30% reduction in the number of steps needed to configure a new dashboard, significantly speeding up the setup process for employees. This initial release marks a critical first step in making the entire workflow more efficient, and future iterations will incorporate user feedback to refine and enhance the solution even further.