B.Sc. (Data Science) Data Visualization Practical Syllabus - Mumbai University

This is the TY BSc Data Science syllabus under NEP 2020, in force from the academic year 2026-27. The University still sets the earlier Choice Based papers alongside it for ATKT candidates, so check which scheme your exam form names before you revise.

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Syllabus for Data Visualization Practical

Vocational skill course · Semester 5 · TY BSc Data Science · 2 credits · 50 marks

Module I: Practical 1: Practical 1: Getting Started with Tableau and Building Basic Visualizations

a Connect to a CSV dataset and explore the Tableau interface
b Identify and differentiate Measures and Dimensions
c Convert fields between discrete and continuous and observe changes
d Create and customize a basic bar chart
e Build a line chart for time-series analysis
f Create a geographic map visualization
g Combine multiple charts into a simple interactive dashboard Practical 2: Working with Data Sources and Data Preparation in Tableau
a Connect to different data sources (Excel, CSV, Database)
b Create and use data extracts vs live connections
c Manage metadata (rename, hide, change data types)
d Perform joins (inner, left, right) on multiple tables
e Apply data blending between two sources
f Implement different types of filters (dimension, measure, date)
g Optimize performance using extracts and filtering Practical 3: Creating Advanced Visualizations in Tableau
a Create stacked and grouped bar charts for comparison
b Build treemaps and pie charts for part-to-whole analysis
c Design scatter plots to identify relationships
d Create dual-axis and combination charts
e Develop histograms for distribution analysis
f Build box-and-whisker plots
g Use Gantt charts and advanced date visualizations Practical 4: Performing Data Analysis using Calculations in Tableau
a Create basic calculated fields using formulas
b Perform row-level calculations
c Perform aggregate-level calculations
d Implement FIXED Level of Detail (LOD) calculations
e Use INCLUDE and EXCLUDE LOD expressions
f Create and use parameters for dynamic analysis
g Apply calculations to fix data issues and enhance insights Practical 5: Analyzing Data using Table Calculations in Tableau
a Apply quick table calculations (running total, percent of total)
b Create moving averages and cumulative metrics
c Perform year-over-year growth analysis
d Use ranking functions (Top N, Bottom N)
e Implement window functions (WINDOW_SUM, WINDOW_AVG)
f Customize addressing and partitioning
g Create dynamic titles and labels using table calculations Practical 6: Designing Effective and Visually Appealing Dashboards
a Apply worksheet-level and workbook-level formatting
b Customize number, date, and null value formatting
c Design effective color schemes and layouts
d Create informative tooltips
e Implement “Viz in Tooltip”
f Improve readability and user experience
g Apply best practices for visual storytelling Practical 7: Creating Interactive Dashboards and Data Stories
a Design a basic dashboard layout using sheets
b Add filters and interactive controls
c Implement highlight and filter actions
d Use URL and set actions for interactivity
e Create dynamic dashboards using parameters
f Design dashboards for multiple devices 1. Build a complete data story using Story feature

Module II: Practical 8: Performing Advanced Analytics using Trends, Clustering, and Forecasting

a Add and interpret trend lines (linear, exponential)
b Customize and analyze trend models
c Perform clustering on datasets
d Analyze distributions using built-in tools
e Apply forecasting techniques
f Compare different statistical models
g Export and interpret statistical results Practical 9: Cleaning and Structuring Data for Analysis
a Identify and handle missing or inconsistent data
b Convert wide data into tall format
c Perform union of multiple files
d Execute cross-database joins
e Restructure data for better visualization
f Handle different levels of detail in datasets
g Apply advanced data cleaning techniques Practical 10: Data Preparation and Transformation using Tableau Prep
a Connect and load data into Tableau Prep
b Clean and profile data
c Group and standardize values
d Merge mismatched fields
e Perform aggregations in Prep
f Apply filters and transformations
g Create and automate data preparation flows Practical 11: Implementing Advanced Visualization Techniques and Customizations
a Create slope charts and lollipop charts
b Design waterfall charts
c Build sparklines for trend analysis
d Implement sheet swapping for dynamic dashboards
e Create custom geographic territories
f Use background images in dashboards
g Apply animation and transparency techniques Practical 12: Sharing, Publishing, and Presenting Data Visualizations
a Export dashboards as PDF/Image
b Use presentation mode in Tableau
c Publish dashboards to Tableau Public
d Share dashboards via Tableau Server/Online
e Enable user interaction on shared dashboards
f Manage permissions and access control
g Evaluate and optimize sharing strategies Practical 13: Retail Sales & Profitability Dashboard Objective: Analyze sales, profit, and discount impact across regions. Key Tasks:
Build bar, line, and map visualizations
Use calculated fields (Profit Ratio)
Apply filters (Region, Category)
Create interactive dashboard Practical 14: Customer Segmentation & Behavior Analysis Objective: Identify customer segments based on purchasing patterns. Key Tasks:
Use clustering
Analyze frequency, recency, and monetary value
Create scatter plots and segmentation dashboards
Highlight high-value customers Practical 15: Sales Forecasting and Trend Analysis Objective: Predict future sales using historical data. Key Tasks:
Build time-series charts
Apply forecasting
Compare seasonal trends
Use moving averages 10 Text Books 1. Learning Tableau 2019 Tools for Business Intelligence, data prep, and visual analytics, Packt Publication 2. Microsoft Power BI Dashboards Errin O’Connor Microsoft Corporation by Pearson Education, Inc. 3. Power BI for the Excel Analyst, Wyn Hopkins, Holy Macro Books, PO Box 541731, Merritt Island FL 32953, USA 2022 11 Reference Books 1. https://learn.microsoft.com/en-us/training/modules/explore-data-power-bi/ 2. https://www.tableau.com/learn/training 3. https://public.tableau.com/en-us/s/resources 12 Internal Continuous Assessment: 40% Semester End Examination: 60% 13 Continuous Evaluation through: 30 marks Semester End Examination Students are expected to attend each practical and submit the written practical of the previous session. Performing Practical and writeup submission will be continuous internal evaluation. 2.5 marks can be awarded for each practical performance and writeup submission totaling to 50 marks and can be converted to 20 marks. 14 Format of Question Paper: Duration 2 hours. Certified copy of Journal is compulsory to appear for the practical examination Practical Slip: Q1. From Module 1 13 marks Q2. From Module 2 12marks Q3. Journal and Viva 05 marks

Text Books

1 Learning Tableau 2019 Tools for Business Intelligence, data prep, and visual analytics, Packt Publication
2 Microsoft Power BI Dashboards Errin O’Connor Microsoft Corporation by Pearson Education, Inc.
3 Power BI for the Excel Analyst, Wyn Hopkins, Holy Macro Books, PO Box 541731, Merritt Island FL 32953, USA 2022
1 https://learn.microsoft.com/en-us/training/modules/explore-data-power-bi/
2 https://www.tableau.com/learn/training
3 https://public.tableau.com/en-us/s/resources

Reproduced from the University of Mumbai syllabus for B.Sc. (Data Science) under NEP 2020, in force from the academic year 2026-27. Wording is as printed in that syllabus. Module numbering is as printed there too.

The complete syllabus

This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.

PDF 2024 25 DS SEM I & II NEP NEP 2020 syllabus, in force from 2024-25 Read full PDF Read

PDF 2023 24 BSc Data Science Sem V & VI Earlier Choice Based syllabus, still set for ATKT candidates Read full PDF Read

PDF 2021 22 BSc Data Science Sem III & IV Earlier Choice Based syllabus, still set for ATKT candidates Read full PDF Read

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