This module will walk you through various methods to access data. The data could be either publicly available or company internal. The module also reviews why it is important for analysts to define clear objectives for their analysis. You will also be introduced to frameworks that help guide digital marketing analysis and their importance to data visualization.

In this module, you will learn an approach to finding patterns in data through visualization. You will see how charts can be used to communicate messages that can be conceptual or data driven and declarative or exploratory. Next, we will learn how to use different charting techniques to reveal data patterns. Visual aids play a major role in identifying ideas and, as a result, we will learn how to match the appropriate visual technique to the ideas we hope to expose. Next, we will explore analysis tools. RStudio is one of the most commonly used tools, and we will explore its visual capabilities. Finally, we will discuss a framework that will help analysts effectively plan for data collection, analysis, and, ultimately, visualization.

This module explores telling stories, through data, that connect emotionally with your audience. It will also review examples and figures that make the concept easy to understand. You will learn the major do’s and don’ts of creating dataviz and rules that lead to the clear depiction of your findings. This unit specifically focuses on Dona Wong’s guidelines for good data visualization and charts. The last leg of Module 4 teaches the three tests that help you improve your visualization. In the final step of dataviz execution, you will learn the McCandless Method for presenting visualizations. This five-step process produces the most effective communication of the graphics to your audience.