This is dataset is for HR analytics. This is a public dataset availble on kaggle, Dataset link: https://www.kaggle.com/datasets/jacksonchou/hr-data-for-analytics I am analyzing this dataset following the steps of the Google data analysis process: ask, prepare, process, analyze, share, and act.
1- ASK:
- Business topic: Tihs dataset contains employee profiles of a large company, where each record is an employee.
- The business task: Demonstrate both predictive logic (why people leave) and prescriptive advice (how to keep them).
- Data: we will use all of the availble coloums as key factors to investigate the business task.
- Stakeholders: Since that is an HR dataset, all the people manages at the company are considred as stakeholders. Executive Leadership (C-level), Department Heads, HR Operations & Talent Acquisition, Finance Department
- Project goal/Metrics: To identify the key drivers of employee attrition and provide data-driven recommendations to improve retention rates and reduce the financial impact of turnover.
2- Prepare
- after going throuhg the dataset using SQL big query, it has no unique ID, we cant check for the duplicates as they might be diffrenet employee with the same data, the data has no null values, and is properly formatted. the dataset is clean, reliable and error-free.
3- Analyze
- Perform descriptive analysis and data profiling on all the numeric values in the dataset to check for outliersor any interesting data points.
- Calculate the turnover rate by divide the number of people who left by the total number of employees.
- correlate a continuous variable "Left" correlation with satisfaction level, last evaluation, number of projects, average monthly hours, time spend at the company.