INTRODUCTION TO BUSINESS ANALYTICS AND DATABASES

Paper Code: 
24MBB321
Credits: 
4
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 

The course will enable students to understand and apply business analytics concepts, processes, and tools, develop database management skills, utilize SQL and MySQL for data manipulation, and implement data warehousing and data mining techniques to support decision-making and business problem-solving.

 

Course Outcomes: 

Course

Learning outcome

(at course level)

Learning and teaching

strategies

Assessment Strategies

Course Code

Course Title

24MBB321

INTRODUCTION TO BUSINESS ANALYTICS AND DATABASES

(Theory)

CO363: Analyse the business problems and examine the application of business analytics in solving such problems.

CO364: Discover the process of business analytics with respect to different case business studies.

CO365: Examine the data models of database for business applications and discuss framework of relational database.

CO366: Design a database for business application and execute queries using MySQL.

CO367: Compare database with Data Warehouse

CO368: Contribute effectively in course-specific interaction

Approach in teaching: Interactive Lectures, Group Discussion, Tutorials, Case Study, Demonstration.

Learning activities for the students:

Self-learning assignments, presentations, practical exercises

Class test, Semester end   examinations, Quiz, Assignments, Presentation, Peer Review

 

12.00
Unit I: 
Business Analytics

Meaning – Data Analytics, Business Analytics, Data Science, Big Data Analytics. Drivers for Business Analytics, Applications of Business Analytics, Skills Required for a Business Analyst.

12.00
Unit II: 
Business Analytics Process and Data Exploration

Business Analytics Life Cycle, Understanding the Business Problem, Collecting and Integrating the Data, Preprocessing the Data, Using Modeling Techniques and Algorithms, Evaluating the Model, Presenting a Management Report and Review.

12.00
Unit III: 
Database

Concept of data, files and database, Database Management Systems, Definition, Characteristics of DBMS, Architecture & Security, Types of Data Models, Concepts, constraints and keys of RDBMS, Introduction to Normalization, 1NF, 2NF and 3NF.

12.00
Unit IV: 
SQL and MySQL

Data definition and Manipulation using MySQL, SQL Process, SQL Commands – DDL, DML, DCL, DQL, SQL Constraints, Data Integrity, Data Types, SQL Operators, Expressions, Querying Database, Retrieving result sets, Sub Queries, Syntax for various Clauses of SQL, Functions and Joins, Indexes, Views, Transactions.

 

12.00
Unit V: 
Data Warehousing

Evolution of Decision Support Systems, Problems with the Naturally Evolving Architecture, Data Warehouse Environment, Definition of data

warehouse, Data marts, Data quality, Data warehouse architecture, ETL tools, Metadata, Cubes and multidimensional analysis, Dimensional data Warehouse, Implement Data Warehouse using MySQL, defining data mining , models and methods for data mining

*Case studies related to entire topics are to be taught.

 

Essential Readings: 
  • Dr. Umesh R. Hodeghatta Umesha Nayak, “Business Analytics Using R - A Practical Approach”, Apress, 2017.
  • Abraham Silberschatz, Henry Korth, S. Sudarshan, “Database Systems Concepts”, 6th Edition, McGraw Hill, 2011.

 

References: 

 

Suggested Readings:

  • W. H. Inmon, “Building the Data Warehouse”, Wiley Dreamtech India Pvt. Ltd., 4th Edition, 2005
  • Carlo Vercellis , Business Intelligence: Data Mining and Optimization for Decision Making, John Wiley & Sons, Ltd. 2009

(Latest editions of the above books are to be referred)

E-Resources Recommended:

Journals Recommended:

 

 

Academic Year: 
2024-2025
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