UNIQUE SERIES AKTU Syllabus
BCDS051

Business Intelligence and Analytics

L-T-P3-0-0 Credits3 Session2024-25 TypeTheory
Appears in 3 semesters · 3 branches

B.Tech Artificial Intelligence & Data Science · Sem 5 (Departmental Elective-I) · B.Tech CSE (Artificial Intelligence) · Sem 5 (Departmental Elective-I) · B.Tech CSE (Data Science) · Sem 5 (Departmental Elective-I)

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Syllabus

5 units · 40 lecture hours
Unit1

Unit 1: BUSINESS INTELLIGENCE – INTRODUCTION

8 hrs

Introduction - History and Evolution: Effective and Timely decisions, Data Information and Knowledge, Architectural Representation, Role of mathematical Models, Real Time Business Intelligent System.

Unit2

Unit 2: BI – DATA MINING & WAREHOUSING

8 hrs

Data Mining - Introduction to Data Mining, Architecture of Data Mining and How Data mining works (Process), Functionalities & Classifications of Data Mining, Representation of Input Data, Analysis Methodologies. Data Warehousing - Introduction to Data Warehousing, Data Mart, Online Analytical Processing (OLAP) – Tools, Data Modelling, Difference between OLAP and OLTP, Schema – Star and Snowflake Schemas, ETL Process – Role of ETL

Unit3

Unit 3: BI – DATA PREPARTTION

8 hrs

Data Validation - Introduction to Data Validation, Data Transformation – Standardization and Feature Extraction, Data Reduction – Sampling, Selection, PCA, Data Discretization

Unit4

Unit 4: BI – DATA ANALYTICS PROCESS

8 hrs

Introduction to analytics process, Types of Analytical Techniques in BI –Descriptive, Predictive, Perspective, Social Media Analytics, Behavioural, Iris Datasets

Unit5

Unit 5: IMPLEMENTATION OF BI

8 hrs

Business Activity Monitoring, Complex Event Processing, Business Process Management, Metadata, Root Cause Analysis.

Course Outcomes (COs)5 outcomes

After completion of the course student will be able to:

  1. CO1Understand the essentials of BI & data analytics and the corresponding terminologiesK2
  2. CO2Analyze the steps involved in the BI - Analytics processK3, K4
  3. CO3Illustrate competently on the topic of analyticsK2, K3
  4. CO4Understand & Implement the K-Means Clustering with Iris DatasetK2, K3
  5. CO5Demonstrate the real time scenario (Case study) by using BI & Analytics techniquesK5, K6

Text Books

  1. Carlo-Vercellis, “Business Intelligence Data Mining and Optimization for Decision-Making”, First Edition
  2. Drew Bentely, “Business Intelligence and Analytics” ,@2017 Library Pres., ISBN: 978-1-9789-2136-8
  3. Larissa T. Moss & Shaku Atre, “Business Intelligence Roadmap: The Complete Project Lifecycle
  4. For Decision-Support Applications”, First Edition, Addison-Wesley Professional,2003
  5. Kimball, R., Ross, M., Thornthwaite, W., Mundy, J., and Becker, B. John, “The Data Warehouse 6. Lifecycle Toolkit: Practical Techniques for Building Data Warehouse and Business Intelligence Systems”, Second Edition, Wiley & Sons, 2008.
  6. Cindi Howson, “Successful Business Intelligence”, Second Edition, McGraw-Hill Education, 2013.

Official AKTU syllabus

This subject is on page 12, 13 of the original AKTU PDF.

Official AKTU syllabus PDF ↗