DATA VISUALIZATION

Paper Code: 
CBDA 514
Credits: 
3
Periods/week: 
6
Max. Marks: 
100.00
Objective: 

This course will enable students to 

1. Understand the interfaces of power BI and Tableau.

2. Learn to design reports and dashboards for data visualisation.
 

Course Outcomes (COs). 

Course outcome (at course level)

Learning and teaching strategies

Assessment Strategies 

 

On completion of this course, the students will;

CO241. Identify the basic features of power BI & tableau tool.

CO242. Able to clean and transform data from different sources.

CO243. Design story board for real life case studies.

CO244. Create static and dynamic charts on datasets.

CO245. Create dashboard based on KPIs of the organization.

Approach in teaching.

Interactive Lectures, Group Discussion, Tutorials, Case Study

 

Learning activities for the students.

Self-learning assignments, Machine Learning exercises, presentations

Class test, Semester end examinations, Quiz, Practical Assignments, Presentation

 

 

18.00
Unit I: 

 

Power BI ecosystem. its relationship with Excel, Power BI suite of products, integration of Power BI products and analytics process flow. Differentiate between the various data sources Connect Power BI to a data source, Clean and transform data to ensure data quality, Load the data to the Power BI Data Model.

 

 

18.00
Unit II: 

 

Introduction to DAX, apply DAX basics in Power BI Desktop, Define DAX formulas, its applications, its syntax rules Create basic calculated columns and measures, Row and Filter Context Apply common DAX expressions such as FILTER, SUM

Page Backgrounds and Templates, create visualizations to display the data, apply drill through and drill down, create and manage slicers with the use of filters. explore visual interactions, Publish the report to the Power BI Service

 

 

18.00
Unit III: 

 

Tableau and Basic Data Analysis in Tableau

Introduction to Tableau, Evaluation of Tableau, Tableau Architecture and Installation of Tableau. Data analysis and data communication with Tableau. Tableau public and desktop. Knowing Your Data, importing data, the “Data Visualization Process”, table view, Dashboard, Tableau Basics. Dimensions, Measures, Tableau Workspace, cards and shelves, marks card, formatting how to analyze structured data using Tableau, exporting data

 

18.00
Unit IV: 

 

Creating Static Charts in Tableau

How to create simple static charts in Tableau , selecting appropriate chart, bar charts, line charts, bubble charts, scatter charts ,tree maps, stacked bar charts, bulleted charts and histogram Visualizing locations and time ,How to save and publish your data in Tableau ,How to export charts from Tableau for use in PowerPoint and Word, reshape data using Tableau. Preparing elevator pitch.

 

18.00
Unit V: 

 

Creating Dynamic Charts in Tableau.

“Measure Names” and “Measure Values” in Tableau, Measures .sum, average, median, minimum ,maximum, standard deviation and variance, removing outliers,  Filters and groups, data hierarchies, trend lines, box plot and regression. Calculations in Tableau, blending and aggregation level calculations, enabling flexibility in KPI. Creating Maps. point maps, shape maps and customize boundary maps.

 

ESSENTIAL READINGS: 
  1. Cole Nussbaumer Knaflic, ”Storytelling with Data. A Data Visualization Guide for Business Professionals”, Wiley,2015.
  2. Daniel G. Murray  ,"Tableau Your Data!. Fast and Easy Visual Analysis with Tableau Software", Wiley,2016.
  3. Nathan Yau," Data Points", Wiley,2013.
  4. Lindy Ryan,"Visual Data Storytelling with Tableau ", Pearson Addison-Wesley Data & Analytics,2018.
  5. Jose Berengueres  , Ali Fenwick and  Marybeth Sandell ,"Introduction to Data Visualization & Storytelling. A Guide For The Data Scientist " , Stokes-Hamilton (29 July 2019)

 

REFERENCES: 
  1. Lindy Ryan,"Visual Data Storytelling with Tableau ", Pearson Addison-Wesley Data & Analytics,2018.
  2. Jose Berengueres  , Ali Fenwick and  Marybeth Sandell ,"Introduction to Data Visualization & Storytelling. A Guide For The Data Scientist " , Stokes-Hamilton (29 July 2019)

 E RESOURCES

  • Tableau official website tutorials:https.//www.tableau.com/
  • My Great Learning Courses on data visualization :https.//www.mygreatlearning.com/academy/learn-for-free/courses/data-visualization-using-tableau

JOURNALS 

 

Academic Year: 
2023-24
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