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Super Admin Dashboard Analytics tab Design

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Prachi Deshpande edited this page Jan 8, 2026 · 25 revisions

Purpose

The purpose of this document is to give an overview of the required visuals that we will be analyzing as part of the Super Admin Dashboard for Saayam functionality task. This includes tracking the activities of beneficiaries, volunteers, voluntary organizations, and donors over periods of time or in terms of geographical location.

Introduction:

There are 3 tabs under the Analytics.
1. Infrastructure
2. Application Analytics
3. Google Analytics

Infrastructure Analytics:

We are going to show one hyperlink of AWS CloudWatch Dashboards which will show all the metrics and dashboards under the AWS CloudWatch for Saayam. Purpose: Under this dashboard tab, we perform the following main activities to monitor and analyze the health of our AWS-based application using AWS CloudWatch.

1. Monitor All Essential AWS Services:
    - We use AWS CloudWatch to monitor all important AWS services used by the application in real time.
    - This includes:
    - API Gateway
    - AWS Lambda
    - AWS Cognito
    - Database services (RDS / DynamoDB)
    - Messaging services (SQS / SNS)
    - Other supporting AWS components
    - CloudWatch continuously collects performance and health metrics from these services.


2. Check for Errors and Warnings:
  - From CloudWatch metrics and logs, we continuously track:
  - Service errors
  - Failures and exceptions
  - Throttling issues
  - High latency warnings
  - Resource over-utilization warnings
  - These errors and warnings help us detect issues early and avoid application downtime.

3. Arrange Services on Priority Basis:
 - All monitored services are automatically arranged based on priority level depending on:
 - Error rate
 - Latency compared to SLA
 - Number of warnings
 - Business impact of the service
 - Priority Levels:
  - Critical
  - High
  - Medium
  - Low

 4. Count Overall Performance of Each Service:
 - This gives a complete picture of how each service is performing.
 - For every AWS service, we calculate and display:
 - Total number of requests
 - Success rate
 - Error rate
 - Average and p95 latency
 - Availability percentage

 5. Use Appropriate Visualizations to Showcase Data:
 - We display all monitoring data using clear and meaningful visualizations, such as:
 - KPI cards for total requests, errors, latency
 - Priority-based service health tables
 - Error & warning trend charts
 - Performance and traffic trend line charts

These visualizations make it easy to:
 - Understand system health quickly
 - Detect problems visually
 - Support fast decision-making

Application Analytics:

    It contains below visuals below per category 

 1. Requests:    
  •	Track the total number of help requests in the past 7 days, month, year or custom range.          
  •	Track the number of help requests by category and region.
 2. KPI for resolving request:   
  •	Average Resolution Time by Category
  •	Number of Requests Resolved, unresolved and in-progress 
 3. Beneficiaries: 
  •	Track the number of beneficiaries in the past 7 days, month, year or custom range.
  •	Break down the number of beneficiaries by country and region.
 4. Volunteers: 
  •	Track the number of volunteers in the past 7 days, month, year or custom range
  •	Break down the number of volunteers by country and region
 5. Organizations: 
  •	Count the total number of organizations involved in the past 7 days, months, year or custom range based on the category (or- profit or Non- profit).
 6. Donors: 
  •	Track active donors over 7 days, month, year, or custom date range based on the country or region.
  •	Calculate the average donation amount per donor across selected periods.

Google Analytics :

Google Analytics (GA4) is used in the Saayam application to track and analyze user interactions across the web app. It helps the team understand how users access and use the platform, without collecting any personal or sensitive information.

We are going to create a hyperlink under the google analytics which can track following things :

  1. Page views across dashboards and modules

  2. User actions such as link clicks, button clicks, and form interactions

  3. Traffic sources (how users reach the app)

  4. Basic usage trends (new vs returning users, device type, location at a high level)

This data supports:

  1. Monitoring overall app usage

  2. Identifying popular features and drop-off points

  3. Improving user experience and navigation

  4. Making data-driven decisions during MVP and post-MVP phases

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