HR Analytics in Tableau

1. HR Analytics in Tableau

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. Working with Tableau

Before we get into analyzing the data, it is important to understand how the end-to-end Tableau development process works. There are four key steps when working with Tableau: connecting and preparing data, building charts and analyzing data, creating dashboards and creating stories.

4. Working with Tableau

For the purpose of this case study, we will be focusing on the first three steps. Creating a story is outside the scope of this case study.

5. Revisiting relationships

Let's recap relationships in Tableau. According to Tableau, relationships are a dynamic, flexible way to combine data from multiple tables for analysis. Now let's refresh ourselves on Cardinality. Cardinality is important in Tableau as it enables us to understand how many unique values or distinct items are in a field or column and how they are related. For example, if the Cardinality of the "Customer ID" field is higher than that of the "Product ID" field, it suggests that there are more unique customers than products in the data set. There are four options: one-to-one, one-to-many, many-to-one, or many-to-many. When creating a relationship between two tables, we must use at least one field to link our tables together.

6. 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. The Atlas Labs HR team wants to be able to monitor key metrics on employees. Their secondary goal is to understand what factors impact employee attrition.

7. Dataset: Employees

For this case study we will build a very simple data model containing three tables. One of the datasets we'll be working with is an Employee table which holds records for all employees past and present. This information includes personal data including name, salary, education, gender, ethnicity, and more. We'll connect this table to our Performance Rating and Education Level table.

8. Dataset: Performance Ratings

Performance Rating is a table that stores information on employees yearly reviews and helps Atlas Labs manage their employees performance on a regular basis. This connects to the Employee table based on Employee ID.

9. Dataset: Education Level

Finally, we have the education level table. This is a small dimension table that provides five rows on education levels such as No formal qualifications, High School etc. We'll connect to the Employee table based on the Education Level ID.

10. Employee connects to PerformanceRating

Here you can see what the model looks like for the Employee and Performance Rating table along with a view of it's relationship, cardinality and related fields.

11. Employee connects to EducationLevel

Similarly, you can see the same setup for the Employee and Education Level table.

12. Let's practice!

Let's test your understanding of working in Tableau.

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