Employee Database ERD and ETL

Background

Project on employees of a corporation over two decades. The task is to create databases off of CSV records that exist for the corporation.

To do this I had to understand the data files, learn how they are interrelated, diagram the relationships, design and build the Schema, import the CSVs into a SQL database, and answer some questions about the data. In short I performed:

1. Data Modeling

2. Data Engineering

3. Data Analysis

Data Modeling

• Inspect the CSVs and sketch out an ERD of the tables.

Data Engineering

• Used the information at hand to create a table schema for each of the CSV files. Set data types, primary keys, foreign keys, and other constraints.
• Import the schema into pgAdmin to create the database and tables
• Import each CSV file into the corresponding SQL table.

Data Analysis

Queried the database for the following questions, approaches included joins, group by, order by, and extracts to derive accurate and meaningful insights:

• List the following details of each employee: employee number, last name, first name, gender, and salary.
• List employees who were hired in 1986.
• List the manager of each department with the following information: department number, department name, the manager's employee number, last name, first name, and start and end employment dates.
• List the department of each employee with the following information: employee number, last name, first name, and department name.
• List all employees whose first name is "Hercules" and last names begin with "B."
• List all employees in the Sales department, including their employee number, last name, first name, and department name.
• List all employees in the Sales and Development departments, including their employee number, last name, first name, and department name.
• In descending order, list the frequency count of employee last names, i.e., how many employees share each last name.
• Import the SQL database into Pandas to conduct additional research and visualize some trends in the data.
• Create a histogram to visualize the most common salary ranges for employees.
• Create a bar chart of average salary by title.

Files Uploaded

• Image of the ERD map for the database
• SQL file of the table schema
• SQL file of the queries above
• Jupyter Notebook file of the import to pandas, additional analysis and charts
• Image outputs saved in the Image folder
• Source CSV's in the data folder