Shehab Dammag

This project demonstrates how to clean, join, and analyse real-world hospital data using SQL. The final output is a Tableau-ready dataset that tracks customer service and patient experience across hospitals in the United States.

## Project Overview

This project is divided into two parts:

1.  **SQL Data Preparation:** Combining and cleaning two datasets:

    1.  HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) survey data.

    2.  Hospital beds data.

2.  **Tableau Dashboard:** Creating an interactive dashboard to visualise hospital performance based on survey responses and hospital sizes.

## Features

*   Cleaning raw data by formatting dates and correcting CMS certification numbers.

*   Handling duplicates by selecting the most recent hospital bed reports.

*   Joining HCAHPS data with hospital bed data for enhanced insights.

*   Exporting the cleaned data to a `.csv` file for use in Tableau.

## Prerequisites

*   PostgreSQL with PGAdmin installed.

*   Tableau (or any data visualisation tool capable of processing `.csv` files).

## Datasets

*   **HCAHPS Data:** Contains survey responses, hospital names, and survey metrics.

*   **Hospital Beds Data:** Contains hospital names, the number of beds, and fiscal year reporting.

## SQL Steps

1.  **Create Tables:**

    1.  Define tables for HCAHPS data and hospital beds data.

2.  **Clean Data:**

    1.  Format dates and pad CMS certification numbers to six digits.

3.  **Handle Duplicates:**

    1.  Use `ROW_NUMBER()` to select the most recent records for each hospital.

4.  **Join Data:**

    1.  Combine the two datasets into one unified dataset.

5.  **Export Data:**

    1.  Save the cleaned dataset as `tableau_file.csv.`



Hospital Data Analysis

As part of my university studies, I created a Task Management Application. Using SQL, Php, Css and Html.

The Task Management Application is a tool designed for businesses and normal users to help keep
work organised and teams in sync. It allows project managers to assign tasks and track progress,
while team members can see their tasks for the day and mark them off when done. It’s secure, easy
to use, and keeps everyone's daily goals clear and manageable. The aim of this application is to make
work life smoother and more productive.

Included a Sign up and Login functionality. Hashed user passwords for safe storage in the database.

![](/images/Screenshot%202024-12-31%20154357.png)

You can create personal tasks for yourself.

![](/images/Screenshot%202024-12-31%20154517.png)

Edit and delete them as you wish

![](/images/Screenshot%202024-12-31%20154604.png)



This is the group section, you will have to name and create a new group. You can assign and unassign tasks to any user on the system, simulating a group and collaborative Task Management Application.

![](/images/Screenshot%202024-12-31%20154710.png)


Task Management Application

Spatial Decision Support System for Hotel Locations in Malaysia

**Overview**

The project integrates hotel and homestay data with Google Maps for a comprehensive spatial decision-making platform. Users can view locations, overlay relevant geographic data, and explore nearby businesses related to tourism, such as restaurants, rental services, and souvenir shops.

The development process was carried out over five weeks, with tasks ranging from data extraction to implementing advanced visualisation features.

**Project Features**

1.  Hotel and Homestay Location Database:

    *   Extracted data from:

        *   [Ministry of Tourism, Arts and Culture Malaysia (MOTAC) Hotel Directory](https://www.motac.gov.my/semakan/hotel-daftar)

        *   MOTAC Homestay Directory (PDF format)

    *   Database fields include:

        *   Name

        *   Full address (street, region, city, etc.)

        *   Longitude and latitude (geospatial coordinates)

2.  Interactive Map Visualisation:

    *   Developed using the Google Maps Platform and React.

    *   Features:

        *   Pinpointing hotel and homestay locations on a map.

        *   Overlaying additional data layers (e.g., rainfall information).

3.  Tourism Business Mapping:

    *   Plotted tourism-related businesses based on Google Maps data, including:

        *   Photography services

        *   Travel and tour agencies

        *   Food and beverage establishments

        *   Rental services (cars, bikes, taxis)

        *   Souvenir shops

        *   Bed and breakfasts

Technical Stack

*   Frontend: React

*   Backend: Node.js

*   APIs: Google Maps API

*   Data Handling: CSV and JSON for database storage

*   Tools: Web scraping, PDF data extraction



Projects

Hospital Data Analysis

Task Management Application

Spatial Decision System