1. HR Analytics in Power BI
Hi, I’m Jess, and I’ll be your instructor on this HR Analytics case study.
2. What is a case study?
A case study enables you to apply your skills.
You won’t be learning any new concepts; instead, you’ll focus on using the skills you learned in previous courses and practice them on a real-world problem.
Below you can see the pre-requisites we suggest you take before completing this case study.
3. Report development in Power BI
Before we get into analyzing the data, it is important to understand how the end-to-end report development process works.
There are four key steps when developing reports in Power BI: building your data model and analyzing data, report design, preparing to share your report, and then sharing your report with your stakeholders.
This process is for Report Development only not necessarily for data analysis.
4. Report development in Power BI
In this case study, we will be focusing on the first two steps.
5. Report development in Power BI
In Step 1 we will focus on 5 key areas: requirements gathering, connecting to data sources, data transformation, building the data model, and writing your initial DAX measures.
6. Report development in Power BI
In Step 2 we will focus on 3 key areas: branding, defining the report layout, and building your report with chart visualizations.
7. Case study goals
The core goal of this case study is to build a report using fictitious datasets from a Tech company called Atlas Labs. Atlas Labs HR team want to be able to monitor key metrics on employees. Their secondary goal is to understand what factors impact employee attrition.
8. The dataset: Fact table
In a typical Power BI report development process we would carry out some form of data modeling. In this case study, using the Kimball Model approach we will be working with facts and dimensions to build our model.
From our dataset, the fact table stores the Performance Ratings. This table contains information about employees yearly reviews and helps Atlas Labs manage their employees performance on a regular basis.
This is the central point of our snowflake schema. It contains 11 different columns and has multiple rows per employee.
9. The dataset: Dimension tables
For this case study we will be working with multiple dimension tables. It enables us to provide more context to the data - the who, what, when, where, and why.
We have five dimension tables that we will be working with: Employee, EducationLevel, RatingLevel, SatisfiedLevel, and Date.
We will be creating the date table in a future exercise and it will contain detailed information such as year, quarter, month, and day.
10. The dataset: Snowflake schema
Our final data model will follow a snowflake schema. We only have one dimension table that doesn't directly attach to the fact table. This is how our final data model will look.
11. Let's practice!
It's time to check your understanding of step 1 in the report development process. Let's practice!