Ui vs api

 In a data-rich engineering web app where GraphQL is used for data retrieval, the time ratio between API development and UI development can vary based on several factors:

1. Data Complexity:If the data structures are complex or have varying relationships, more time might be spent on API development to ensure efficient querying and data retrieval.

2. UI Customization Needs: When the UI requires extensive customization for each section or table, additional time might be allocated to UI development to ensure each component meets specific requirements.

3. Integration Challenges:Bridging the gap between the GraphQL responses and UI components, especially in scenarios where components cannot be easily reused, can significantly impact the time spent on integration efforts.

4. Functionality and User Interactions: If the application involves complex user interactions, form handling, validations, or real-time updates, a considerable amount of time may be dedicated to implementing these features in the UI layer.

5. Testing and Optimization:Both the API and UI layers require thorough testing, but the complexity and breadth of the UI might demand more time for testing and optimization. 

Let's delve into the statistics and a more detailed example of an engineering data app with multi-level JSON data, emphasizing the UI complexities:

Development Time Breakdown:

- UI Development Time: Reports suggest UI/UX development often consumes about 50-70% of the total project time for applications handling complex data structures. This includes creating components, managing state, and ensuring data flow between parent-child components.

- Backend (GraphQL API) Time: Meanwhile, GraphQL API development typically accounts for 20-30% of the total time. This phase focuses on schema design, resolvers, and ensuring efficient data retrieval.

Example: Engineering Data App - Multi-level JSON Data:

Imagine an engineering monitoring dashboard powered by GraphQL. It presents hierarchical data structures like equipment, subsystems, and sensor readings.

- UI Complexity:

   - Nested Components:Representing multi-level JSON data involves creating nested components to display different levels of information. For instance, a dashboard might contain equipment cards showing subsystems, and each subsystem might have sensor data visualization components.

   

   - Data Communication:Ensuring seamless communication between parent and child components to populate and update data accurately requires intricate state management and event handling.

- GraphQL Integration:

   - GraphQL Queries:Utilizing GraphQL queries to fetch hierarchical data can simplify data retrieval. However, mapping this data effectively onto various UI components requires meticulous handling to match each component's requirements.

Impact on User Experience and Business:

- User Experience: A well-designed UI that effectively translates complex data into intuitive visualizations ensures engineers can swiftly comprehend critical information, reducing the risk of errors and improving decision-making.

- Business Impact:A subpar UI that fails to efficiently display multi-level engineering data may lead to confusion or misinterpretation, potentially impacting operational efficiency or even safety protocols. Conversely, a user-friendly interface significantly enhances productivity and reduces the likelihood of errors.

In engineering applications dealing with multi-level JSON data, UI development takes precedence due to its intricacies in handling nested components and ensuring smooth data communication. While GraphQL aids in data retrieval, it's the effective translation of this data into an intuitive interface that truly elevates user experience, impacting the success of the application in critical operational settings.

As a generalized estimate, in data-rich engineering web apps leveraging GraphQL, the time ratio might lean towards spending slightly more time on UI development and integration (potentially around 1.5x to 2x) compared to the API development phase. However, this ratio can significantly vary based on the specific project's requirements, complexities, and the team's expertise in GraphQL, Angular, and overall application development.