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AKTU Business Intelligence and Analytics (BCDS051) Syllabus PDF – B.Tech 3rd Year
Business Intelligence and Analytics BCDS051
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Official AKTU syllabus of Business Intelligence and Analytics (BCDS051) for B.Tech 3rd Year – 3 credits, L-T-P 3-0-0. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Business Intelligence and Analytics
Download PDFBCDS051 · 3 credits · L-T-P 3-0-0
Course Outcomes
At the end of course, the student will be able to:
| CO 1 | Understand the essentials of BI & data analytics and the corresponding terminologies | K 2 |
| CO 2 | Analyze the steps involved in the BI - Analytics process | K K 3, 4 |
| CO 3 | Illustrate competently on the topic of analytics | K , K 2 3 |
| CO 4 | Understand & Implement the K-Means Clustering with Iris Dataset | K K 2, 3 |
| CO 5 | Demonstrate the real time scenario (Case study) by using BI & Analytics techniques | K , K 5 6 |
Course Content
L-T-P: 3-0-0
| Unit | Topic | Proposed Lecture |
|---|---|---|
| I | BUSINESS INTELLIGENCE – INTRODUCTION: Introduction - History and Evolution: Effective and Timely decisions, Data Information and Knowledge, Architectural Representation, Role of mathematical Models, Real Time Business Intelligent System. | 8 |
| II | BI – DATA MINING & WAREHOUSING: 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 | 8 |
| III | BI – DATA PREPARTTION: Data Validation - Introduction to Data Validation, Data Transformation – Standardization and Feature Extraction, Data Reduction – Sampling, Selection, PCA, Data Discretization | 8 |
| IV | BI – DATA ANALYTICS PROCESS - Introduction to analytics process, Types of Analytical Techniques in BI –Descriptive, Predictive, Perspective, Social Media Analytics, Behavioral, Iris Datasets | 8 |
| V | IMPLEMENTATION OF BI: Business Activity Monitoring, Complex Event Processing, Business Process Management, Metadata, Root Cause Analysis. | 8 |
Text Books
- Carlo-Vercellis, “Business Intelligence Data Mining and Optimization for Decision-Making”, First Edition
- Drew Bentely, “Business Intelligence and Analytics” ,@2017 Library Pres., ISBN: 978-1-9789-2136-8
- Larissa T. Moss & Shaku Atre, “Business Intelligence Roadmap: The Complete Project Lifecycle
- For Decision-Support Applications”, First Edition, Addison-Wesley Professional,2003
- 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.
- Cindi Howson, “Successful Business Intelligence”, Second Edition, McGraw-Hill Education, 2013.
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