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Introduction to Business Analytics: Communicating with Data

University of Illinois at Urbana-Champaign via Coursera

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  • Provider Coursera
  • Subject Business Intelligence
  • $ Cost Free Online Course (Audit)
  • Session In progress
  • Language English
  • Certificate Paid Certificate Available
  • Effort 4-6 hours a week
  • Start Date
  • Duration 4 weeks long

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Overview

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This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.

Syllabus

WEEK 1

Module 1

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.

 

WEEK 2

Module 2

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.

 

WEEK 3

Module 3

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.

 

WEEK 4

Module 4

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.

 

Taught by

Kevin Hartman

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