Data Visualization and Business Intelligence

Course Information

• Course Title: Data Visualization and Business Intelligence
• Course Code: DVBI101

Course Description

This course provides an introduction to data visualization techniques and tools for effective business intelligence. Students will learn to analyze and present data visually to gain insights and support decision-making processes. The course covers principles of data visualization, explores various visualization techniques, and introduces popular business intelligence tools.

Learning Objectives

By the end of the course, students will be able to:

1. Understand the principles and importance of data visualization in business intelligence.
2. Identify appropriate visualization techniques based on data characteristics and analysis goals.
3. Use popular data visualization tools to create interactive and compelling visual representations.
4. Analyze and interpret visualized data to extract meaningful insights.
5. Apply effective storytelling techniques to present data visually in a business context.

Course Outline

Module 1: Introduction to Data Visualization

• Understanding data visualization and its role in business intelligence
• Principles of effective data visualization
• Overview of data visualization tools and technologies

Module 2: Data Types and Visualization Techniques

• Understanding different data types and their visualization requirements
• Graphical techniques for categorical data
• Visualization techniques for numerical and time-series data
• Handling textual and geospatial data visualization

Module 3: Data Visualization Tools

• Introduction to popular data visualization tools (e.g., Tableau, Power BI)
• Exploring data visualization tool features and functionalities
• Creating static and interactive visualizations using data visualization tools

Module 4: Data Exploration and Analysis

• Exploratory data analysis techniques for visualizing relationships and patterns
• Using data visualization for trend analysis and forecasting
• Visualizing statistical measures and distributions

Module 5: Storytelling with Data Visualization

• Principles of data storytelling and narrative visualization
• Designing effective data visualizations for storytelling
• Presenting and communicating data insights through visualizations

Module 6: Business Intelligence and Dashboard Design

• Introduction to business intelligence concepts and applications
• Designing interactive dashboards for data-driven decision making
• Dashboard best practices and usability considerations

Evaluation and Grading

• Assignments: 40%
• Projects: 30%
• Midterm Examination: 15%
• Final Examination: 15%

Textbook and Resources

• Required Textbook: [We will provide the reference materials]
• Supplementary Resources: [List of supplementary resources]

Academic Integrity and Policies

• Academic Integrity: Students are expected to uphold academic integrity and avoid plagiarism or cheating. Refer to the university’s academic integrity policy for more information.
• Attendance: Attendance and active participation in class discussions and activities are strongly encouraged.
• Late Submissions: Late submissions may be subject to a grade penalty unless an extension is granted in advance.
• Grading Policy: The instructor will provide detailed grading criteria and rubrics for assignments and projects.