Refactor The Dashboard Mocked Data To Dynamic Backend Served Data

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As a management company employee, having an interactive admin portal dashboard containing dynamic data specific to the apartment complex you're managing is crucial for efficient decision-making and effective property management. In this article, we will explore the process of refactoring the dashboard mocked data to dynamic backend served data, ensuring that the Upcoming Renewals, Pending Leases, and Apartments Info tables display accurate and up-to-date information.

Understanding the Requirements

To create an interactive admin portal dashboard, we need to consider the following requirements:

  • Upcoming Renewals Table: The table should display dynamic data fetched from the server, including the apartment number, lease start date, lease end date, and renewal status.
  • Pending Leases Table: The table should display dynamic data fetched from the server, including the apartment number, lease start date, lease end date, and lease status.
  • Apartments Info Table: The table should display dynamic data fetched from the server, including the apartment number, unit type, square footage, and rent amount.
  • Interactive Buttons and Parts: All buttons and interactive parts in the Upcoming Renewals, Pending Leases, and Apartments Info tables should work and result in dynamic interactions.

Refactoring the Dashboard Mocked Data

To refactor the dashboard mocked data to dynamic backend served data, we need to follow these steps:

Step 1: Design the Database Schema

The first step is to design the database schema to store the apartment complex data. The schema should include the following tables:

  • Apartments: This table will store information about each apartment, including the apartment number, unit type, square footage, and rent amount.
  • Leases: This table will store information about each lease, including the apartment number, lease start date, lease end date, and lease status.
  • Renewals: This table will store information about each renewal, including the apartment number, lease start date, lease end date, and renewal status.

Step 2: Create the Backend API

The next step is to create the backend API to fetch and update the data in the database. The API should include the following endpoints:

  • GET /apartments: This endpoint will return a list of all apartments in the database.
  • GET /leases: This endpoint will return a list of all leases in the database.
  • GET /renewals: This endpoint will return a list of all renewals in the database.
  • POST /apartments: This endpoint will create a new apartment in the database.
  • POST /leases: This endpoint will create a new lease in the database.
  • POST /renewals: This endpoint will create a new renewal in the database.

Step 3: Implement the Frontend Logic

The final step is to implement the frontend logic to fetch and display the data from the backend API. We can use a JavaScript library like React or Angular to create the frontend application.

Example Code

Here is an example of how we can implement the frontend logic using React:

import React, { useState, useEffect } from 'react';
import axios from 'axios';

function ApartmentsInfo() {
    const [apartments, setApartments] = useState([]);

    useEffect(() => {
        axios.get('/apartments')
            .then(response => {
                setApartments(response.data);
            })
            .catch(error => {
                console.error(error);
            });
    }, []);

    return (
        <table>
            <thead>
                <tr>
                    <th>Apartment Number</th>
                    <th>Unit Type</th>
                    <th>Square Footage</th>
                    <th>Rent Amount</th>
                </tr>
            </thead>
            <tbody>
                {apartments.map(apartment => (
                    <tr key={apartment.id}>
                        <td>{apartment.apartmentNumber}</td>
                        <td>{apartment.unitType}</td>
                        <td>{apartment.squareFootage}</td>
                        <td>{apartment.rentAmount}</td>
                    </tr>
                ))}
            </tbody>
        </table>
    );
}

export default ApartmentsInfo;

Conclusion

Refactoring the dashboard mocked data to dynamic backend served data is a crucial step in creating an interactive admin portal dashboard. By following the steps outlined in this article, we can create a robust and scalable backend API and implement the frontend logic to fetch and display the data from the backend API. With this approach, we can ensure that the Upcoming Renewals, Pending Leases, and Apartments Info tables display accurate and up-to-date information, enabling effective property management and decision-making.

Future Improvements

There are several future improvements that we can make to the dashboard:

  • Implement Data Validation: We can implement data validation to ensure that the data entered by the user is accurate and valid.
  • Add Data Filtering and Sorting: We can add data filtering and sorting capabilities to the dashboard to enable the user to quickly find and analyze specific data.
  • Implement Real-time Updates: We can implement real-time updates to the dashboard to enable the user to see changes to the data as they occur.
  • Add User Authentication and Authorization: We can add user authentication and authorization to the dashboard to ensure that only authorized users can access and modify the data.

In our previous article, we explored the process of refactoring the dashboard mocked data to dynamic backend served data. In this article, we will answer some frequently asked questions about this process.

Q: What is the main difference between mocked data and dynamic backend served data?

A: Mocked data is a static dataset that is used to simulate the behavior of a real application. Dynamic backend served data, on the other hand, is a real dataset that is fetched from a backend API. The main difference between the two is that mocked data is not updated in real-time, whereas dynamic backend served data is updated in real-time as the data changes in the backend API.

Q: Why is it necessary to refactor the dashboard mocked data to dynamic backend served data?

A: Refactoring the dashboard mocked data to dynamic backend served data is necessary because it allows the dashboard to display accurate and up-to-date information. With mocked data, the dashboard may display outdated or incorrect information, which can lead to poor decision-making. By using dynamic backend served data, the dashboard can display the most current information, enabling effective property management and decision-making.

Q: What are the benefits of using dynamic backend served data in the dashboard?

A: The benefits of using dynamic backend served data in the dashboard include:

  • Accurate and up-to-date information: Dynamic backend served data ensures that the dashboard displays accurate and up-to-date information, enabling effective property management and decision-making.
  • Improved user experience: Dynamic backend served data provides a better user experience by allowing users to see changes to the data as they occur.
  • Increased productivity: Dynamic backend served data enables users to quickly find and analyze specific data, increasing productivity and efficiency.

Q: How can I implement dynamic backend served data in my dashboard?

A: To implement dynamic backend served data in your dashboard, you can follow these steps:

  1. Design the database schema: Design the database schema to store the apartment complex data.
  2. Create the backend API: Create the backend API to fetch and update the data in the database.
  3. Implement the frontend logic: Implement the frontend logic to fetch and display the data from the backend API.

Q: What are some common challenges that I may face when implementing dynamic backend served data in my dashboard?

A: Some common challenges that you may face when implementing dynamic backend served data in your dashboard include:

  • Data validation: Ensuring that the data entered by the user is accurate and valid.
  • Data filtering and sorting: Implementing data filtering and sorting capabilities to enable users to quickly find and analyze specific data.
  • Real-time updates: Implementing real-time updates to the dashboard to enable users to see changes to the data as they occur.
  • User authentication and authorization: Implementing user authentication and authorization to ensure that only authorized users can access and modify the data.

Q: How can I troubleshoot issues with dynamic backend served data in my dashboard?

A: To troubleshoot issues with dynamic backend served data in your dashboard, you can follow these steps:

  1. Check the backend API: Check the backend API to ensure that it is functioning correctly and returning the expected data.
  2. Check the frontend logic: Check the frontend logic to ensure that it is correctly fetching and displaying the data from the backend API.
  3. Check the database schema: Check the database schema to ensure that it is correctly designed and storing the expected data.

By following these steps and troubleshooting common issues, you can ensure that your dashboard is displaying accurate and up-to-date information, enabling effective property management and decision-making.

Conclusion

Refactoring the dashboard mocked data to dynamic backend served data is a crucial step in creating an interactive admin portal dashboard. By answering these frequently asked questions, we can ensure that we have a clear understanding of the process and can implement it successfully. With this approach, we can create a robust and scalable backend API and implement the frontend logic to fetch and display the data from the backend API.