You'll start this Tableau case study by importing and cleaning the job posting dataset and checking for missing values. Once you’ve done this, it’s time to roll up your sleeves and do some initial data exploration.

Job market analysis in Tableau

Options

In Scope

Out of scope

EDA questions to ask

Importing data

Initial EDA

Job postings trend analysis

Data filtering of job titles

Salary vs. years of experience

True

False

Trends found with EDA

Exploratory Analysis

In this chapter, you’ll continue to apply your Tableau skills to extract data insights with filtering techniques, interesting visualizations, and trend analysis. The DataSearch team still needs answers. Luckily, they have you on their team!

Market insight analysis

Key insights to focus on

Job skills analysis

Demand vs. supply by experience level

Column splitting

Deep dive into key job descriptions

Trends from analysis

Analyzing Market Trends

It’s almost time to hand over the final deliverable. In this final chapter, you’ll combine all of the job-related insights you’ve discovered into an interactive Tableau dashboard for the DataSearch team.

Building job market analysis dashboard

How to design a dashboard

Creating your first dashboard

Adding KPIs

Less is more

Adding the last visual

Final clean up and insights

Case study wrap-up

Dashboards and Insights

Workbooks and Datasources

Metadata sheet

In this Tableau case study, you’ll explore a real-world job posting dataset to uncover insights for a fictional recruitment company called DataSearch. Using what you’ve learned from previous courses, you’ll use visualization techniques to investigate the data to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

You’ll start by importing and cleaning a dataset, making sure it’s prepared for data exploration. You’ll then use filters and calculated fields to build insightful visualizations of your findings, allowing for trend analysis. Finally, you’ll bring it all together using Tableau's powerful dashboard capabilities so that you can answer questions for the DataSearch team.

By practicing the techniques you’ve learned so far, this Tableau case study gives you the chance to get some hands-on practice with a dataset. Once you’ve finished the course, you’ll be more confident using Tableau to present your data insights.


<h2>Utilize Your Skills with a Tableau Case Study</h2>
In this Tableau case study, you’ll explore a real-world job posting dataset to uncover insights for a fictional recruitment company called DataSearch. Using what you’ve learned from previous courses, you’ll use visualization techniques to investigate the data to find out what skills are most in-demand for data scientists, data analysts, and data engineers.
<br><br>
<h2>Use Tableau to Gain Data Insights</h2>
You’ll start by importing and cleaning a dataset, making sure it’s prepared for data exploration.
You’ll then use filters and calculated fields to build insightful visualizations of your findings, allowing for trend analysis.
<br><br>
<h2>Create Tableau Dashboards to Present Your Work</h2>
Finally, you’ll bring it all together using Tableau's powerful dashboard capabilities so that you can answer questions for the DataSearch team.
<br><br>
By practicing the techniques you’ve learned so far, this Tableau case study gives you the chance to get some hands-on practice with a dataset. Once you’ve finished the course, you’ll be more confident using Tableau to present your data insights.

Creating Dashboards in Tableau

In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

Case Study: Analyzing Job Market Data in Tableau

Analist de date în Tableau

Job postings over the past 5 years are trending upward.

As years of experience increase for a job, so does the associated salary.

There are many empty values for salary information.

There is no correlation between job position level (i.e., Entry level, Director, Internship) and years of experience for a job.

Data Science Manager is the most popular and in demand role in data science.

Trends found with EDA

Case Study: Analyzing Job Market Data in Tableau

Exercițiu interactiv practic