BN4101 Managerial Decision Science Syllabus:
BN4101 Managerial Decision Science Syllabus – Anna University PG Syllabus Regulation 2021
OBJECTIVES:
➢ To understand the role of Data Analytics in Decision making
➢ To familiarize the Spreadsheets in Data management and Visualization
UNIT – I INTRODUCTION
Role of Data Analytics in Decision Making, Business Analytics and Classification. Understanding the significance of data-driven decision-making in modern business, Influence of analytics on managerial decisions, Data analytics lifecycle, Choosing the right tool for the right task. Introduction to Spreadsheets, Data Visualisation and Project Management Tools, Setting up software tools and resources.
UNIT – II SPREADSHEETS FOR DATA ANALYSIS
Spreadsheets for Data Analysis: Spreadsheets as fundamental data analysis tool, Basic operations, data entry, and cell references, Using formulas and functions for data manipulation. Understanding PivotTables and their role in data summarization, Creating PivotTables and Pivot Charts, Customizing PivotTables for effective analysis. Using advanced Spreadsheet functions (e.g., VLOOKUP, IF, INDEX-MATCH).
UNIT – III DATA VIZUALIZATION
Principles of effective data visualization. Choosing the right chart type for different data scenarios. Customizing charts for clarity. Creating Advanced Charts in Spreadsheets, Building advanced charts (e.g., trendlines, combo charts, and waterfall charts). Case studies and exercises applying advanced functions.
UNIT – IV INTERACTIVE REPORTS AND DASHBOARDS
Introduction to Data Visualization platforms, Data Import and Transformation, Building Interactive Reports and Dashboards, Creating Visualizations (Bar charts, Pie charts, etc.), Slicers and Filters, Sharing and Collaboration of data, Fundamentals of Tableau, Connecting to Data Sources, Creating Interactive Dashboards, Advanced Visualizations (Maps, Heatmaps, etc.), Calculations and Parameters in Tableau, Data Storytelling with Tableau
UNIT – V OTHER TOOLS
Basics of Project Management, Using popular Tools to understand Project Interface and Basics, Task Scheduling and Dependencies, Resource Allocation and Tracking, Gantt Charts and Reporting, Tracking project progress and updates.
TOTAL: 45 PERIODS
COURSE OUTCOMES:
➢ Appreciate the significance of Data Analytics in Business Decision making.
REFERENCES:
1. U Dinesh Kumar, “Business Analytics: The Science of Data-driven Decision Making”,Wiley India, 2020.
2. Sanjiv Jaggia, Alison Kelly, Kevin Lertwachara and Leida Chen, Business Analytics. Tata McGraw Hill 2nd Edition,2023.
3. Anil Maheswari, Data Analytics, Anil Maheswari, 2nd Edition, McGraw Hill, 2023.
4. James R. Evans, “Business Analytics – Methods, Models and Decisions”, Pearson Ed, 2012.
5. Manaranjan Pradhan, Dinesh Kumar, “Machine Learning using Python”, Wiley, 2019
6. Wayne Winston (2017). Microsoft Excel 2016 Data Analysis and Business Modelling, 5th Edition
7. Uma Maheswari, Sujatha, “Introduction to Data Science: Practical approach with R and Python’, Wiley, 2021.
8. “Learning Tableau”, Joshua N. Milligan, Packt Publications, 2022.
9. “Practical Tableau”, Ryan Sleeper, O’Reilly Media, Inc. 2018.
10.“Mastering Microsoft Power BI”, Brett Powell