Data Visualization and Reporting - Course Syllabus PDF
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Uploaded by WondrousNewOrleans
Loyalist College
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Summary
This document provides a syllabus and course information for a course on data visualization and reporting. It outlines the course structure, assessment methods, and materials, including the textbook "The Big Book of Dashboards". The course includes topics such as data visualization, presentation, collaborative learning, and using tools such as Tableau.
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DATA VISUALIZATION AND REPORTING DAB201 Embark on a journey to transform data into compelling visual stories! Contact Office Hours: Monday 11:00 AM to 12:00 PM EST Tuesday 12:00 PM to 01:00 PM EST Thursday 11:00 AM to 12:00 PM EST Fr...
DATA VISUALIZATION AND REPORTING DAB201 Embark on a journey to transform data into compelling visual stories! Contact Office Hours: Monday 11:00 AM to 12:00 PM EST Tuesday 12:00 PM to 01:00 PM EST Thursday 11:00 AM to 12:00 PM EST Friday 12:00 PM to 02:00 PM EST Students are encouraged to make an appointment for office hours and 1:1 meetings. (By Appointment Only) Class Rules and Expectations Respect everyone in the class. Treat others the way you want to be treated, with kindness and respect. All email correspondence to the instructor must be through the SCC email system. Please remember to turn off all cell phones while in class and utilize laptops for academic purposes only. Class will begin on time every day. If you are late, you are expected to come in quietly without disrupting your classmates. It is your responsibility to find out what you missed from someone else in the class. I suggest that you arrange for a “homework buddy” who can collect handouts and let you know what you missed. You will only be permitted an extension on tests and/or the submission of a hard copy of assignments if you provide one of the following pieces of documentation: Doctor’s note Bereavement notice Copy of a summons or subpoena Proof of call for military service No exceptions!!! About This Course Core Concepts Practical Application Collaborative Learning Storytelling with Data Visualization Tools Mastery Insightful Analysis Approach Educational Strategy: Dynamic Lectures: We'll dive into the essentials of DatVisulization, its evolution, and its modern-day applications. Practical Engagements: Through active projects, we'll translate AI theory into practice. Team-Based Exploration: We'll leverage collaborative learning to enhance understanding and innovation. Assessment Weight Toward Final Grade Exam 1 25.00% Frequency: 1 Description: Exam will contain application exercises and may also include Evaluation multiple choice questions, true/false, and or short answer questions. Outcomes Assessed: 1, 2, 3, 4. EES Assessed: 1. Exam 2 25.00% 1. Grading: Frequency: 1 | Description: The exam will contain application exercises and may also A = 80 - 100% include multiple choice questions, true/false, and or short answer questions. B = 70 - 79% Outcomes Assessed: 5, 6, 7, 8. C = 60 - 69% EES Assessed: 1. Lab Assignments 25.00% D = 50 59% Frequency: 5 F = Less than 50% Description: Lab exercises require students to work on different datasets using various tools. Outcomes Assessed: 2, 3, 4, 5, 6, 8. Note on Rounding: EES Assessed: 1, 2, 6, 7. Scores of x.5% or higher will be Project 25.00% Frequency: 1 rounded up to the next grade (e.g., Description: Students will perform end-to-end analyses of a dataset using 79.5% becomes 80%, 59.5% the various tools and techniques learned in the course. becomes 60%). Outcomes Assessed: 2, 3, 4, 5, 6, 7, 8. Scores below x.5% will remain at EES Assessed: 1, 2, 6, 7, 9, 10. Total 100% the lower grade. Class schedule and Syllabus Textbooks: 1. "The Big Book of Dashboards" by Steve Wexler, Jeffrey Shaffer, and Andy Cotgreave Course Additional Resources: Online Platforms: Access to online data visualization Materials communities and forums. Software Tools: Introduction to Tableau for data visualization and analysis. and LinkedIn Learning: LinkedIn platform for additional learning and examples. Resources Tableau Learning: In-Class Hands-On Learning: Interactive sessions with Tableau. Tableau Online Resources: Access to Tableau tutorials, guides, and official documentation. Practical Exercises: Real-world scenarios for practice using Tableau. What is Definition: The graphical representation of information Data and data. Significance: Visualization Transforms complex data sets into understandable and interpretable visuals. Enhances the ability to detect patterns, trends, and outliers in large data sets. Facilitates more effective data analysis and decision-making. The Power of Visualization Benefits of Visualization: Simplifies complex data. Reveals hidden insights. Supports effective decision-making Image credit - Link Data visualization allows us to quickly interpret and make sense of complex data. https://www.ablebits.com/office-addins-blog/make-bar-graph-excel/ Elements of Data Visualization Key Elements: Clarity: Ensuring the visualization is easy to understand. Accuracy: Representing data truthfully and precisely. Aesthetics: Visually appealing to engage the audience. “The goal of visualization is insight, Functionality: Serving its intended purpose effectively. not pictures" – Ben Shneiderman In the left example, the chart design is cluttered. In the right example, many clutter elements have been addressed to enhance how the chart communicates. https://www.effectivedatastorytelling.com/post/a-data-storytellers-guide-to-avoiding-clutter Choosing the Right Type of Visualization Criteria for Selection: Data Type: Quantitative vs. Qualitative. Audience: Technical expertise and information needs. Story: The message or insight you want to convey. Why Do We Table with four groups of numbers: What do they tell you? Visualize Data? Why Do We Why Do We Visualize Data? Visualize Data?
