JNTUH CSE-AIML DATA WAREHOUSING AND BUSINESS INTELLIGENCE SYLLABUS

JNTUH CSE-AIML DATA WAREHOUSING AND BUSINESS INTELLIGENCE SYLLABUS

Course Objectives:
1. This course is concerned with extracting data from the information systems that deal with the day-to-day operations and transforming it into data that can be used by businesses to drive  high-level decision making
2. Students will learn how to design and create a data warehouse, and how to utilize the process
of extracting, transforming, and loading (ETL) data into data warehouses.
Course Outcomes:
1. Understand architecture of data warehouse and OLAP operations.
2. Understand Fundamental concepts of BI and Analytics
3. Application of BI Key Performance indicators
4. Design of Dashboards, Implementation of Web Analytics
5. Understand Utilization of Advanced BI Tools and their Implementation.
6. Implementation of BI Techniques and BI Ethics.
UNIT – I
DATA WAREHOUSE: Data Warehouse-Data Warehouse Architecture- Multidimensional Data ModelData cube and OLAP Technology-Data Warehouse Implementation -DBMS schemas for Decision support – Efficient methods for Data cube computation.
UNIT – II
Business Intelligence: Introduction – Definition, Leveraging Data and Knowledge for BI, BI Components, BI Dimensions, Information Hierarchy, Business Intelligence and Business Analytics. BI Life Cycle. Data for BI – Data Issues and Data Quality for BI.
UNIT – III
BI Implementation – Key Drivers, Key Performance Indicators and Performance Metrics, BI Architecture/Framework, Best Practices, Business Decision Making, Styles of BI-vent-Driven alerts-A
cyclic process of Intelligence Creation. The value of Business intelligence -Value driven and Information
use.
UNIT – IV
Advanced BI – Big Data and BI, Social Networks, Mobile BI, emerging trends, Description of different BI-Tools (Pentaho, KNIME)
UNIT – V
Business intelligence implementation-Business Intelligence and integration implementation-connecting
in BI systems- Issues of legality- Privacy and ethics- Social networking and BI.
TEXT BOOKS:
1. Data Mining – Concepts and Techniques – JIAWEI HAN & MICHELINE KAMBER, Elsevier.
2. Rajiv Sabherwal “Business Intelligence” Wiley Publications, 2012.
REFERENCE BOOKS:
1. Efraim Turban, Ramesh Sharda, Jay Aronson, David King, Decision Support and Business Intelligence Systems, 9th Edition, Pearson Education, 2009.
2. David Loshin, Business Intelligence – The Savy Manager’s Guide Getting Onboard with Emerging IT, Morgan Kaufmann Publishers, 2009.

3. Philo Janus, Stacia Misner, Building Integrated Business Intelligence Solutions with SQL Server, 2008 R2 & Office 2010, TMH, 2011.
4. Business Intelligence Data Mining and Optimization for decision making [Author: Carlo-Verellis][Publication: (Wiley)]
5. Data Warehousing, Data Mining & OLAP- Alex Berson and Stephen J. Smith- Tata McGrawHill Edition, Tenth reprint 2007
6. Building the Data Warehouse- W. H. Inmon, Wiley Dreamtech India Pvt. Ltd.
7. Data Mining Introductory and Advanced topics –MARGARET H DUNHAM, PEA.

CSE-AIML

SEMESTER SUBJECT CODE SUBJECT Lession Plan Lecturer Notes & Question Bank SYLLABUS ABOUT TUTOR
I MA101BS Mathematics – I Click Here
I AP102BS Applied Physics Click Here
I CS103ES Programming for Problem Solving Click Here
I ME104ES Engineering Graphics Click Here
I AP105BS Applied Physics Lab Click Here
I CS106ES Programming for Problem Solving Lab Click Here
I MC109ES Environmental Science Click Here
II MA201BS Mathematics – II Click Here
II CH202BS Chemistry Click Here
II EE203ES Basic Electrical Engineering Click Here
II ME205ES Engineering Workshop Click Here
II EN205HS English Click Here
II CH206BS Engineering Chemistry Lab Click Here
II EN207HS English Language and Communication Skills Lab Click Here
II EE208ES Basic Electrical Engineering Lab Click Here
II-I CS310PC Discrete Mathematics Click Here
II-I CS302PC Data Structures Click Here
II-I MA313BS Mathematical and Statistical Foundations Click Here
II-I CS304PC Computer Organization and Architecture Click Here
II-I CS311PC Python Programming Click Here
II-I SM306MS Business Economics & Financial Analysis Click Here
II-I CS307PC Data Structures Lab Click Here
II-I CS312PC Python Programming Lab Click Here
II-I MC309 Gender Sensitization Lab Click Here
II-II CS416PC Formal Language and Automata Theory Click Here
II-II CS417PC Software Engineering Click Here
II-II CS403PC Operating Systems Click Here
II-II CS404PC Database Management Systems Click Here
II-II CS412PC Object Oriented Programming using Java Click Here
II-II CS406PC Operating Systems Lab Click Here
II-II CS407PC Database Management Systems Lab Click Here
II-II CS408PC Java Programming Lab Click Here
II-II MC409 Constitution of India Click Here
III-I Design and Analysis of Algorithms Click Here
III-I Machine Learning Click Here
III-I Computer Networks Click Here
III-I Compiler Design Click Here
III-I Graph Theory (PE1) Click Here
III-I Introduction to Data Science(PE1) Click Here
III-I Web Programming(PE1) Click Here
III-I Image Processing(PE1) Click Here
III-I Computer Graphics(PE1) Click Here
III-I Software Testing Methodologies(PE2) Click Here
III-I Information Retrieval Systems(PE2) VIJAYANAND S
III-I Pattern Recognition(PE2) Click Here
III-I Computer Vision and Robotics(PE2) Click Here Click Here
III-I Data Warehousing and Business Intelligence(PE2) Click Here
III-I Machine Learning Lab Click Here
III-I Computer Networks Lab Click Here
III-I Advanced Communication Skills Lab Click Here
III-I Intellectual Property Rights Click Here
III-II Artificial Intelligence Click Here Click Here
III-II DevOps Click Here Click Here
III-II Natural Language Processing Click Here Click Here
III-II Internet of Things(PE3) Click Here Click Here
III-II Data Mining(PE3) Click Here Click Here
III-II Scripting Languages(PE3) Click Here Click Here
III-II Mobile Application Development(PE3) Click Here Click Here
III-II Cryptography and Network Security(PE3) Click Here Click Here
III-II Artificial Intelligence and Natural Language Processing Lab Click Here Click Here
III-II DevOps Lab Click Here Click Here
IV-I Neural Networks & Deep Learning Click Here Click Here
IV-I Reinforcement Learning Click Here Click Here
IV-I Quantum Computing(PE4) Click Here Click Here
IV-I Expert Systems(PE4) Click Here Click Here
IV-I Cloud Computing(PE4) Click Here Click Here
IV-I Game Theory(PE4) Click Here Click Here
IV-I Mobile Computing(PE4) Click Here Click Here
IV-I Expert Systems(PE4) Click Here Click Here
IV-I Cloud Computing(PE4) Click Here Click Here
IV-I Game Theory(PE4) Click Here Click Here
IV-I Mobile Computing(PE4) Click Here Click Here
IV-I Social Network Analysis(PE5) Click Here Click Here
IV-I Federated Machine Learning(PE5) Click Here Click Here
IV-I Augmented Reality & Virtual Reality(PE5) Click Here Click Here
IV-I Web Security(PE5) Click Here Click Here
IV-I Ad-hoc & Sensor Networks Click Here Click Here
IV-I Deep Learning Lab Click Here Click Here
IV-II Organizational Behaviour Click Here Click Here
IV-II Speech and Video Processing(PE6) Click Here Click Here
IV-II Robotics Process Automation(PE6) Click Here Click Here
IV-II Randomized Algorithms(PE6) Click Here Click Here
IV-II Cognitive Computing(PE6) Click Here Click Here
IV-II Semantic Web(PE6) Click Here Click Here

Add Comment

Your email address will not be published. Required fields are marked *

Style switcher RESET
Body styles
Color settings
Link color
Menu color
User color
Background pattern
Background image