B.Des-Data Visualization and Data Science

B.Des – Data Visualization and Data Science

The Bachelor of Design (B.Des) in Data Visualization and Data Science is a future-focused undergraduate programme that combines design thinking, data analytics, artificial intelligence, and visual communication. Students learn to transform complex data into meaningful visual experiences that support business decisions, scientific research, and digital innovation.

The programme emphasizes analytical thinking, storytelling with data, interactive dashboard design, information graphics, UI/UX design, business intelligence, and emerging AI technologies to prepare graduates for the rapidly growing data-driven economy.

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What You Will Learn

  • Data Visualization
  • Data Science Fundamentals
  • Information Design
  • UI/UX Design
  • Data Analytics
  • Artificial Intelligence
  • Machine Learning Basics
  • Dashboard Design
  • Business Intelligence
  • Python for Data Analysis
  • Design Thinking
  • Visual Storytelling

Career Opportunities

  • Data Visualization Specialist
  • Data Analyst
  • Business Intelligence Analyst
  • Information Designer
  • UX Designer
  • Data Storytelling Specialist
  • Analytics Consultant
  • Design Researcher
Aspect Data Analyst Data Visualization Expert
Core Function Examines data to find patterns, answer questions, and make predictions. Designs how data and insights are visually presented so people can understand and act quickly.
Nature Analytical – focuses on what the data says and why. Communicative – focuses on how to show the data and to whom.
Primary Goal Produce accurate insights and recommendations based on data. Turn insights into clear, intuitive visuals that drive decisions and action.
Typical Questions "What happened?", "Why did it happen?", "What will happen next?", "What should we do?" "Who needs to see this?", "What do they need to decide?", "How can they grasp it in 5 seconds?"
Input Raw datasets, databases, logs, transaction records. Processed metrics, key insights, user needs, decision contexts.
Output Tables, statistical models, written reports, forecasts, recommendations. Dashboards, charts, infographics, interactive visual interfaces, visual alerts.
Approach Uses statistics, query languages, and models to analyze and interpret data. Uses design principles, layout, color, and interaction patterns to encode information visually.
Key Skills Statistics, SQL, programming (Python/R), hypothesis testing, critical thinking. Visual design, information design, UX/UI, storytelling, layout, typography, color theory.
Typical Tools SQL, Excel, Python/R, statistical packages, BI tools for analysis. Tableau, Power BI, Figma/Sketch, D3.js/other visualization libraries, dashboard builders.
Creativity Analytical creativity (new metrics, new ways to slice data). Visual and narrative creativity (new ways to represent and explain data).
Duration 4 Years (8 Semesters)
Affiliation Anna University
Approval AICTE Approved
Anna University Counselling Code 2361

Graduates of this programme are equipped with industry-relevant skills and may pursue opportunities with leading global organizations such as:

Note: Company names are indicative of potential employers for graduates with relevant skills and experience. They do not represent confirmed placement partnerships or guaranteed recruitment.