Course Overview
Data Visualization represents data and information in a visual context or graphics, such as a graph, chart, map, picture, plot, infographic, or animation. It is a way to make data easier for the human brain to understand. The goal is to make it easier to understand the data and to identify patterns, trends, and outliers. The course over the 11-week period will focus on the ways visualization is used and the skills to apply to informatics.
Week 1: Introduction to Data Visualization – The main topics that are included in a Data Analyst position are data management, data analysis, and data reporting. Data visualization is the graphical representation of information and data and is included in all three topics. This course focuses on the variety of visual presentations and how they are used to manage data, analyze data and report data results.
Week 2: Visual Communication and Thinking – Much of our communication is visual and some people will process data better when it is presented as a picture or diagram rather than words and numbers, written or spoken. This section reviews the basics of communication and how we process information.
Week 3: Types of Media and Channels – Visual communication is more complex than we first think it is. This section covers the rules and characteristics of working with visuals. The type of media used can have an impact on the delivery of the messages and the channel is the method by which the visual is presented to the viewer.
Week 4: Displaying Visual Data – This week we start to apply what we know about visual thinking, communication, and presentation of data using charts, pictures, and graphs. This section defines some common rules about presenting data, and what needs to be included when making a chart.
Week 5: Graphical Analysis/ Decisions – When we collect data in healthcare, we need to use the data to determine what is going on and what will happen in the future. The primary function of analysis is to identify significance and trends. We can use graphical analysis to identify factors and their impact on the results and to view patterns that give insight into future events.
Week 6: Complex Data Visualization – This section focuses on how complex data is managed and presented. One topic in this section is understanding the relationship between variables to produce a visual representation of cause and effect. Other complex relations are networks. This section also defines how pivot tables are used to classify and group data and the process of setting up a pivot table in Excel.
Week 7: Data Maps – This section focuses on using shapes and pictures to convey communication and meaning. Many analytics programs rely on two-dimensional comparison of data to define meaning, data maps use physical structure and layouts as a framework to convey meaning.
Week 8: Dashboards and Infographics – This section covers a collection of data outcomes and results which are presented together to report or analyze a specific theme or message. The current term is an information radiator and is a primary means of communication progress to an operational team or leadership. Another topic to cover is infographics, a set of pictures that may include words, numbers, graphs, and pictures, arranged in a way that is easy for the viewer to interpret.
Week 9: Visual Management and Facilitation – Visual management is using pictures, colors, and signals to monitor and control work. Many times, analysis is a collection of data at a fixed point in time, a snapshot of the process. There are types of data visualization that account for time and movement. This section reviews collecting and displaying time over the course of time, and ways that data management can be used to monitor actions and provide control to ensure quality. Visual facilitation is also covered here, using pictures to get groups to work together to make decisions and innovate. Using pictures can be used during brainstorming or team-building creative processes. This section also reviews the design thinking process and how pictures are means of designing and planning.
Week 10: Animation and video – This section adds the concept of moving pictures to apply to data visualization. Contrasting video and animation to still images, the benefits and challenges are reviewed here.
Week 11: Challenges in Data Visualization – This section focuses on some of the drawbacks or limitations of visual messages. In some cases, the message itself is misleading or creates confusion. There are also significant limitations for classes of viewers that need to be considered when creating a visual message.
