University of Illinois at Urbana-Champaign
Introduction to Business Analytics: Communicating with Data
University of Illinois at Urbana-Champaign

Introduction to Business Analytics: Communicating with Data

This course is part of multiple programs.

Taught in English

Some content may not be translated

Kevin Hartman
Unnati Narang

Instructors: Kevin Hartman

45,537 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.6

(568 reviews)

|

96%

Beginner level
No prior experience required
15 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

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Assessments

5 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.6

(568 reviews)

|

96%

Beginner level
No prior experience required
15 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

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There are 4 modules in this course

This module, will help you earn the foundation needed to become a good data communicator. After completion of this module, you will know the history of data visualizaiton, understand today’s dataviz tools, make connections with visuals, and evaluate the effectiveness of data visualizations.

What's included

7 videos8 readings2 quizzes1 peer review1 discussion prompt1 plugin

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.

What's included

5 videos2 readings1 quiz1 peer review

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.

What's included

5 videos2 readings1 quiz1 peer review

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.

What's included

6 videos4 readings1 quiz1 peer review1 plugin

Instructors

Instructor ratings
4.6 (162 ratings)
Kevin Hartman
University of Illinois at Urbana-Champaign
5 Courses220,791 learners

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