Data Analysis and Visualization (CACS 455) — Exam Pattern Analysis [2025–2022]
These question variations are provided only to help you understand the exam pattern and how topics are asked, not exam predictions.
Note on 2022 paper: The 2022 question paper (Q12–Q20) contains Operations Research topics (LPP, Simplex Method, Transportation, Assignment, Game Theory, Queuing) that do not appear in the current CACS 455 syllabus. Only Q11 from 2022 is mapped to this syllabus. This is likely a paper mismatch or a legacy syllabus variant. Analysis below covers only questions that fall within the current Data Analysis and Visualization syllabus.
1. Topics and Their Questions
Importance and Role of Data Visualization
Question Variations
- What is data analysis and visualization? Explain the general methods of solving OR model. [2022]
- What are the importances of data visualization? What are the impacts of proper use of colors in data visualization? [2025]
Visual Analytics
Question Variations
- Explain different types of visual analytics in detail. [2025]
Hierarchical Data Visualization
Question Variations
- How hierarchical data can be visualized? Explain the techniques in detail. [2025]
Visual Mapping
Question Variations
- What is visual mapping? How can we perform visual mapping? [2025]
Scalar Fields in Spatial Data Visualization
Question Variations
- What is scalar field in data visualization? Explain applications of it. [2025]
Software Tools and Datasets
Question Variations
- Explain about Detroit dataset. Also explain the suitable visualization technique to visualize this dataset. [2025]
Short Notes (Visual Encoding, Types of Maps, Tableau)
Question Variations
- Write short notes on: (Any two) — a) Visual encoding b) Types of maps c) Tableau [2025]
Text Data Visualization and Levels of Text Representation
Question Variations
- Explain different levels of text representation. Also explain different techniques for text data visualization in detail. [2025]
Spatial Data Visualization — Marks and Channels
Question Variations
- What are the importances of spatial data visualization? How different kinds of marks and channels can be used in spatial data visualization? Explain. [2025]
Non-Spatial Data Visualization — Separate, Order, Align and Word Cloud
Question Variations
- How separate, order and align can be used in non-spatial data visualization? Explain word cloud for data visualization. [2025]
2. Study Priority
Topics that appear most frequently across papers. Only 2 papers were available for this subject under the current syllabus.
| Topic | Chapter | Priority | Frequency | Years Appeared |
|---|---|---|---|---|
| Importance and Role of Data Visualization | Unit 1 — Introduction to Visualization | High | 2x | [2025, 2022] |
| Visual Analytics | Unit 2 — Creating Visual Representations | Important | 1x | [2025] |
| Visual Mapping | Unit 2 — Creating Visual Representations | Important | 1x | [2025] |
| Hierarchical Data Visualization (Tree Data, Hierarchical Structures) | Unit 3 — Non-Spatial Data Visualization | Important | 1x | [2025] |
| Text Data Visualization and Levels of Text Representation | Unit 3 — Non-Spatial Data Visualization | Important | 1x | [2025] |
| Separate, Order, Align and Word Cloud | Unit 3 — Non-Spatial Data Visualization | Important | 1x | [2025] |
| Scalar Fields and Applications | Unit 4 — Spatial Data Visualization | Important | 1x | [2025] |
| Marks and Channels in Spatial Visualization | Unit 4 — Spatial Data Visualization | Important | 1x | [2025] |
| Detroit Dataset and Visualization Techniques | Unit 5 — Software Tools and Data for Visualization | Important | 1x | [2025] |
| Visual Encoding, Types of Maps, Tableau (Short Notes) | Unit 1 / Unit 4 / Unit 5 | Important | 1x | [2025] |
3. Most Repeated Questions
Based on available papers (2022 and 2025), only one topic — the importance and definition of data visualization — appeared across both years. No questions appeared with nearly identical wording.
| Question / Concept | Years Appeared | Frequency |
|---|---|---|
| Definition / importance of data visualization (asked differently each year) | [2025, 2022] | 2x |
4. Chapter Frequency [2025–2022]
| Chapter | Number of Questions | Main Topics Covered |
|---|---|---|
| Unit 1 — Introduction to Visualization | 2 | Definition of data visualization, importance, use of color, perceptual issues |
| Unit 2 — Creating Visual Representations | 2 | Visual analytics, visual mapping, visualization reference model |
| Unit 3 — Non-Spatial Data Visualization | 3 | Hierarchical structures (tree data), text representation levels, text data techniques, word cloud, separate/order/align |
| Unit 4 — Spatial Data Visualization | 2 | Scalar fields and applications, marks and channels in spatial visualization, types of maps |
| Unit 5 — Software Tools and Data for Visualization | 2 | Detroit dataset, Tableau, visualization tool selection |
5. Cold Topics
These topics appeared only once across [2025–2022] papers. Note: with only two papers available and the 2022 paper largely off-syllabus, almost all topics are single-appearance. Topics listed here are ones that may have low recurring priority based on current evidence.
| Chapter | Topic | Year |
|---|---|---|
| Unit 1 — Introduction to Visualization | Impact of proper use of colors in data visualization | 2025 |
| Unit 2 — Creating Visual Representations | Design of visualization applications | 2025 |
| Unit 3 — Non-Spatial Data Visualization | Time series data characteristics and mapping of time | Not yet asked |
| Unit 3 — Non-Spatial Data Visualization | Scatter plot and quantitative values visualization | Not yet asked |
| Unit 3 — Non-Spatial Data Visualization | Graph drawing and labeling rules | Not yet asked |
| Unit 4 — Spatial Data Visualization | Isocontours and Topographic Terrain Maps | Not yet asked |
| Unit 4 — Spatial Data Visualization | Direct Volume Rendering and Multidimensional Transfer Functions | Not yet asked |
| Unit 4 — Spatial Data Visualization | Vector fields | Not yet asked |
| Unit 5 — Software Tools and Data for Visualization | Iris dataset, Breakfast Cereal dataset, Dow Jones Industrial Average dataset | Not yet asked |
| Unit 5 — Software Tools and Data for Visualization | Python, MATLAB, Java for visualization | Not yet asked |