Introduction to Business Analytics and Databases

Paper Code: 
MBB 126
Credits: 
4
Contact Hours: 
60.00
Max. Marks: 
100.00
Objective: 

Course Outcomes (COs):

Courseoutcome

Learning andteachingstrategies

AssessmentStrategies

  

On completion of this course, the students will be able to;

CO 31.Analyse the business problems and examine the application of business analytics in solving such problems.

CO 32.Discover the process of business analytics with respect to different case business studies.

CO 33.Examine the data models of database for business applications and discuss framework of relational database.

CO 34.Design a database for business application and execute queries using MySQL.

CO 35.Compare database with Data Warehouse

CO 36.Design a Data Warehouse for business application using MySQL.

 

Approach inteaching:InteractiveLectures,GroupDiscussion,Tutorials, CaseStudy,Demonstration.

Learningactivitiesforthestudents:

Self-learningassignments,presentations,practicalexercises

Classtest,Semester endexaminations, Quiz,Assignments,Presentation, PeerReview

  

 

12.00

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

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

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

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

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. HodeghattaUmeshaNayak, “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: 
2022-2023
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