Data Visualization with Tableau Specialization Review - Is it worth it?

In this modern age with large data and technology, data visualization is becoming a more important in-demand job among companies since they need to analyze that data and visualize them to get more information about their customers, revenue, and more. Data visualization is the process of converting a large amount of data into charts to have a more clear view of what’s going inside your company, as they say, a picture worth a thousand words. Learning these skills is a must in many job fields if you are going to be a data analyst, data scientist, machine learning engineer, and many other fields, just to name a few. There are many software and programming languages such as python and R to make data visualization.

Still, they are for technical people who have experience in programming. Still, you can use a simple and powerful software known as Tableau to make a a beautiful representation of your data, and o of the best courses to learn this software is Data Visualization with Tableau Specialization program.

Review - Is Data Visualization with Tableau Specialization on Coursera worth it?

Now, let's find out whether Data Visualization with Tableau Specialization is worth your time and money or not by finding out who is teaching, I mean your instructor and what is taught, I mean course content and structure. 

1. The Instructors Review

The course offered by the University of California ranked as one of the highest research universities in the USA and a global leader in many fields such as medicine, science, technology, and more. They created the course by experts in the California university, such as Govind Acharya, a principal analyst, and many other instructors, to have a good experience after finishing the program.

2. Course Content

Now, let's checkout what is cover in this specialization 

2.1. Fundamentals of Visualization with Tableau

Without any experience or technical knowledge, you can start taking the course to learn what data visualization is and discuss why it is important and installing the Tableau public. Next, you start learning the Tableau interface like the dashboard screen and the Tableau worksheet.

 Later, you will learn to create simple charts such as line charts, treemaps, and bar charts. Finally, you will discover where you will get help if you faced a problem and get inspiration for data visualization.

2.2. Essential Design Principles for Tableau

This the section will start by understanding how the human brain perceives the world and the differences between effective and infective visualization. Also, you will understand the different types of visualization and how to improve ineffective visualization. 

Next, you will learn the visual & cognitive principles, define the ideas of exploratory & exploratory analysis, and define outliers in your data. Finally, you will learn how to define your audience and define the connection between data.

2.3. Visual Analytics with Tableau

After you’ve created some charts in the first section and learned few things about the visualization, you will advance your skills more here more charting using Tableau such as dual charts, and learn what is Tableau tooltip is and when to use it. 

Next, you will understand the differences between the discrete and continuous data, learn about table calculation, and create new calculated fields to compare many fields. Finally, learn about mapping in Tableau and customize them by changing colors, shapes, and size.

2.4. Creating Dashboards and Storytelling with Tableau

You will start this section by understanding what a story is, which you will explain your visualization when you are sharing it with your team and the importance of planning before you start. 

Next, you will identify the key metrics that will answer your business and learn how to use dashboards in Tableau to tell your story and the best practices to use it and apply a filter, action within Tableau.

Finally, you will deep dive more about how to better tell your story by looking to a wide range of examples and techniques.

2.5. Data Visualization with Tableau Project

The the last course in this specialization is for creating a project based on what you’ve learned in the past four courses by following the steps of creating a data visualization that you have seen, starting by developing a project proposal then importing and preparing the data for visualization. 

Later, you will apply exploratory analysis of your data and create the visualization. Finally, create and share the story with your team.

Conclusion

Data visualization is a hot topic nowadays, and more companies are demanding these skills for many job fields. It is important to have more views and understanding of your data to move to the next step by applying machine learning algorithms on your data or any actions you want.