Job market analysis in Tableau
1. Job market analysis in Tableau
Hi! I’m Shivali, your instructor for this case study. I work as a Business Analyst and use Tableau to share findings and insights with my colleagues. In my spare time, I like to write songs. So with that, let's dive in!2. What is a case study?
A case study allows you to apply the skills you've learned from previous courses on a particular topic. It also allows you to work on a problem that those in data science commonly work to solve. For this, no new concepts will be introduced beyond what was covered in the prerequisite courses.3. Data analysis process with Tableau
This case study will follow the data analytics process: doing a data check and exploration of the data, analyzing and visualizing the data, building the final dashboard and communicating insights. Let's explore these steps more in-depth.4. Data analysis process with Tableau
For this first chapter, you will be performing an integrity check of the data and also start the exploratory data analysis. Towards the later exercises for this chapter, you will get into asking business questions related to the problem we will be working to solve.5. Data analysis process with Tableau
For the second chapter, you will go deeper into analyzing the dataset using more advanced techniques. Specifically, you will be using many types of visualizations and some basic calculated fields for even further analysis.6. Data analysis process with Tableau
For the last chapter, you will be building out the visualizations in a more intuitive and user-friendly method for our key stakeholders. Tableau is designed for this, so we'll be taking advantage of this tool's many features to best display our insights. Note that communicating insights, as in publishing your dashboards, is beyond the scope of this case study.7. Problem to solve
You will be working for an employer recruiting firm, called DataSearch, to find insights into market trends of jobs in data science. Recruiters, also known as headhunters, perform employment recruiting services for both companies and those looking to gain employment. You'll be tasked to use a dataset of job postings to find trends in top data science jobs along with associated skills.8. The data
For this case study, you will be using a fictitious dataset that is comprised of job postings over the past 5 years for the Data and Analytics industry. Each entry in the table of this dataset correlates to a specific job posting in time, which has 19 attributes or columns for each posting. One important disclaimer on this dataset is that because it's fictitious, please don't apply any insights gained during this case study into the real world.9. The data
The dataset is comprised of both qualitative and quantitative characterized columns. For the qualitative columns, the primary columns include items relevant to a job posting, such as the ID, title, type, and level, along with the required skills for the job.10. The data
For the quantitative columns we will be looking at attributes such as dates of job postings, minimum experience level requested in years, minimum and maximum salary offered for the job posting, and the number of applicants that applied to the job in the first 24 hours. Note you can also download the dataset and the metadata sheet from the course overview page if you want to work in your local version of Tableau.11. Final deliverable
As a sneak peek into our final deliverable in the last chapter; here are some snapshots of the dashboards that we will be working to build!12. Let's practice!
Now it's time to get our Tableau gloves on! Let's practice.Create Your Free Account
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