Skip to content

Using advanced SQL techniques and Tableau visualization, this project explores workforce dynamics, managerial structures, and potential salary disparities within an organization's employee database. A flexible SQL stored procedure enhances the analysis, fostering a data-driven approach to organizational insights.

Notifications You must be signed in to change notification settings

ranayalcink/HR_Analytics-sql-tableau

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 

Repository files navigation

SQL Project - HR Data Analytics

Business Problem

Objective: Extract Actionable Insights from Employee Database

In this data analysis project, the business problem revolves around unraveling intricate patterns within the company's employee database. Key objectives include understanding workforce demographics, managerial structures, and discerning potential gender-based salary disparities.

Used skills:

  • SQL Querying
  • Data Analysis
  • Data Visualization (Tableau)
  • Stored Procedure Development
  • Database Management
  • Data Aggregation
  • Conditional Logic
  • Dynamic Parameterization
  • Problem Solving
  • Tableau Dashboard Development
  • Interactive Data Exploration

Technical Approach

Chart 1: Gender Breakdown Over Time

SQL Query:

  • Utilizes a JOIN operation to combine t_employees and t_dept_emp tables.
  • Extracts calendar year, gender, and employee count.
  • Facilitates GROUP BY for aggregating data by year and gender.

Chart 2: Male and Female Managers Comparison

SQL Query:

  • Employs subqueries and JOIN operations to link multiple tables (t_employees, t_dept_manager, t_departments) for comprehensive data retrieval.
  • Utilizes a CASE statement for categorizing active managers based on their tenure.

Chart 3: Average Salary Comparison by Gender and Department

SQL Query:

  • Leverages JOIN operations to integrate salary, employee, and departmental data.
  • Applies GROUP BY for aggregating data by department, gender, and calendar year.
  • Implements the HAVING clause to filter results for the specified time frame.

Stored Procedure: Salary Filtering

SQL Stored Procedure:

  • Implements a stored procedure named filter_salary.
  • Accepts user-defined minimum and maximum salary values.
  • Utilizes WHERE clause to filter salary data within the specified range.
  • Empowers users to dynamically explore average male and female salaries per department.

Practical Application

As a data analyst, this project equips stakeholders with actionable insights to inform strategic decision-making. By harnessing the power of SQL queries and a versatile stored procedure, we not only answer predefined questions but also empower users to explore the data autonomously. This approach aligns with the principles of data-driven decision-making, fostering a more inclusive and informed organizational culture.

Tableau Dashboard

In addition to the SQL analyses, a Tableau dashboard was created to visually represent the key insights derived from the SQL queries. The dashboard provides an interactive and user-friendly interface for stakeholders to explore the data visually. It complements the SQL-driven analysis by offering a dynamic and intuitive way to interpret the findings.

Conclusion

The SQL portfolio project exemplifies the value of leveraging data analytics to address real-world business challenges. Through thoughtful analysis and visualization, we have provided a lens into workforce dynamics, leadership structures, and salary trends. As a data analyst, this project reflects a commitment to delivering actionable insights that drive positive change within the organization.

About

Using advanced SQL techniques and Tableau visualization, this project explores workforce dynamics, managerial structures, and potential salary disparities within an organization's employee database. A flexible SQL stored procedure enhances the analysis, fostering a data-driven approach to organizational insights.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published