DATA VISUALIZATION TOOLS

Paper Code: 
DCAI 704A
Credits: 
06
Periods/week: 
12
Max. Marks: 
100.00
Objective: 

This course will enable students to: 

1. learn the concepts of data analysis with the tool R.

2. understand the interfaces of power BI and Tableau.

3. design reports and dashboards for data visualization.

 

Learning Outcome

Learning and Teaching Strategies

Assessment Strategies-

The students will:

CO106. Apply analysis tool R to solve practical problems in a variety of disciplines

CO107.  Identify the basic features of power BI & tableau.

CO108. Clean and transform data from different sources.

CO109. Design storyboard for real life case studies.

CO110. Create static and dynamic charts on datasets.

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

R

  • Introduction to R Studio, Logical Arguments, Missing Values, Characters, Factors and Numeric, Help  in R, Vector to Matrix, Matrix Access.  Data Frames, Data Frame Access, Basic Data Manipulation Techniques, Usage of various apply functions – apply, lapply, sapply and tapply, Outliers treatment.
  • Charts (Bar, Pie, Histogram), Measures of Central Tendency and Measures of dispersion

Power BI

  •  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.
  • 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

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 analyse structured data using Tableau, exporting data
  • Creating Static and Dynamic 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, reshape data using Tableau. Preparing elevator pitch. Measures. sum, average, median, minimum, maximum, standard deviation and variance, removing outliers, Filters and groups, data hierarchies, trend lines, box plot and regression.

 

 

ESSENTIAL READINGS: 
  • Srivasa K.G., Siddesh G M,Shetty,” Statistical Programming in R”, Oxford University Press 2017
  • Cole Nussbaumer Knaflic, ”Storytelling with Data. A Data Visualization Guide for Business Profesionals”, Wiley,2015.
  •  Daniel G. Murray  ,"Tableau Your Data!. Fast and Easy Visual Analysis with Tableau Software", Wiley,2016.
  • Nathan Yau," Data Points", Wiley,2013.
  • Lindy Ryan,"Visual Data Storytelling with Tableau ", Pearson Addison-Wesley Data & Analytics,2018.
  • Jose Berengueres  , Ali Fenwick and  Marybeth Sandell ,"Introduction to Data Visualization & Storytelling. A Guide For The Data Scientist " , Stokes-Hamilton (29 July 2019)

 

REFERENCES: 

SUGGESTED REFERENCE BOOKS:

  • Cotton, Richard(2016) Learning R: A Step-by-Step Function Guide to Data Analysis
  • Lindy Ryan,"Visual Data Storytelling with Tableau ", Pearson Addison-Wesley Data & Analytics,2018.
  • 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 INCLUDING LINKS:

  • R Tool Spoken Tutorial: https://spoken-tutorial.org/
  • 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

 REFERENCE JOURNALS:

 

Academic Year: 
2023-24
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