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