Google Data Analytics Certificate Course 6 Review: Share Data Through the Art of Visualization

Course 6 of the Google Data Analytics Certificate focuses on data visualization—arguably the most visible part of an analyst's work.

This is where your analysis becomes something stakeholders can actually use. No matter how good your insights are, they're worthless if nobody understands them.

What Course 6 Covers

Visualization principles - What makes effective charts (and what makes misleading ones)
Tableau basics - Hands-on with Tableau Public
Dashboard creation - Building interactive views
Storytelling with data - Connecting visuals to narrative
Design for your audience - Executives need different views than analysts

What I Liked

Tableau Introduction

Getting hands-on with Tableau is valuable. It's one of the most in-demand visualization tools in job postings, and this course provides a solid foundation.

You'll build actual dashboards, not just watch someone else build them. That hands-on practice matters.

Design Principles

The course covers important concepts like:

Choosing the right chart type for your data
Avoiding misleading visuals (truncated axes, cherry-picked time periods)
Designing for your audience (what works in a meeting vs what works in an email)
Color theory and accessibility

These are timeless principles that apply to any visualization tool.

Pre-Attentive Attributes

They introduce the concept of pre-attentive attributes—visual elements your brain processes before conscious thought (color, size, position).

Understanding this helps you guide your audience's attention to what matters most. I use these principles constantly.

Limitations

Surface-Level Tableau

You learn the basics, but Tableau mastery requires much more practice. After this course, you can build simple dashboards. You can't build complex, production-ready analytics yet.

Consider this a starting point, not the finish line.

Limited Tool Coverage

Tableau is great, but you'll likely also need:

Power BI (very common in Microsoft-heavy enterprises)
Python visualization libraries (matplotlib, seaborn, plotly)
Excel charts (still heavily used for simple reporting)

The principles transfer, but each tool has its own learning curve.

Not Enough Practice

Like most courses in the certificate, you get enough practice to understand the concepts but not enough to build muscle memory. Plan to build side projects after completing Course 6.

My Recommendation

Visualization skills are essential for any analyst. This course gives you enough foundation to be dangerous.

After Course 6, build 3-5 dashboards using public datasets. Kaggle has tons of practice data. Publish them to Tableau Public and add them to your portfolio.

That additional practice will cement the skills and give you something to show in interviews.

The Bottom Line

Course 6 delivers on its promise: you'll understand how to share data effectively through visualization.

The Tableau skills are valuable. The design principles are even more valuable—they'll serve you across any tool you use in your career.

Common Questions About Course 6

Q: Do I need to pay for Tableau to complete this course?

No. They use Tableau Public, which is free. You'll only need paid Tableau if you're working with private company data in a real job.

Q: How long does Course 6 take?

Google estimates 23 hours. Budget 25-30 if you're new to visualization concepts. Take your time with the design principles—they're more important than the tool mechanics.

Q: Will this course make me job-ready for data visualization roles?

No. It'll give you foundational skills. Job-ready means building complex dashboards, understanding database connections, and designing for production use. That takes additional practice.