Introduction to Data Visualization for Data Analysts

Übersicht

Data is the new gold—no doubt about it. But how do you mine to find it?

In this course, Introduction to Data Visualization for Data Analysts, you’ll learn how to create high-impact, high-quality data visualizations that effectively find and expose golden nuggets hidden in data. First, you’ll explore the fundamentals of data visualization, including its definition and the key components of compelling visual representations.

Next, you’ll dive into the data visualization workflow, gaining the skills to transform raw data into meaningful visual stories. Finally, you'll discover how data visualizations can solve real-world problems using industry-standard tools like Excel, Power BI, and Tableau.

When you’re finished with this course, you'll have the expertise to present complex data in a clear, visually engaging way, making it accessible to non-technical audiences.

Lehrplan

• Introduction to Data Visualization
Definition of data visualization
Importance and benefits of visualizing data
Overview of different types of data visualizations
• Key Components of Effective Data Visualizations
Understanding your audience
Principles of design in data visualization (color, layout, typography)
Best practices for clear and accurate communication
• Data Visualization Workflow
Data collection and preparation
Choosing the right visualization type for your data
Using storytelling techniques to convey messages
• Tools for Data Visualization
Overview of Excel, including charts and pivot tables
Introduction to Power BI for interactive dashboards
Getting started with Tableau for advanced data visualization
• Practical Applications of Data Visualization
Case studies of data visualization solving real-world problems
Transforming raw data sets into visual stories
• Hands-On Projects
Creating visualizations using sample data sets in Excel
Developing a Power BI dashboard for business intelligence
Building a data story using Tableau
• Presenting Data Visually
Techniques for presenting data to non-technical audiences
Overcoming common challenges and pitfalls in data presentations
• Conclusion and Course Wrap-up
Recap of key learnings
Resources for further learning
Final project showcasing skills acquired in the course

---

Unterrichtet von

Ben Howard

---

Fachgebiete

Data Science