CCS341 DATA WAREHOUSING Anna University Syllabus Regulation 2021

CCS341 DATA WAREHOUSING 

Anna University Syllabus Regulation 2021

CCS341 DATA WAREHOUSING                                                                             L T P C 

                                                                                                                                       2 0 2 3 

COURSE OBJECTIVES: 

• To know the details of data warehouse Architecture 
• To understand the OLAP Technology 
• To understand the partitioning strategy 
• To differentiate various schema 
• To understand the roles of process manager & system manager 

UNIT I INTRODUCTION TO DATA WAREHOUSE                                                      5 

Data warehouse Introduction - Data warehouse components- operational database Vs data warehouse – Data warehouse Architecture – Three-tier Data Warehouse Architecture - Autonomous Data Warehouse- Autonomous Data Warehouse Vs Snowflake - Modern Data Warehouse 

UNIT II ETL AND OLAP TECHNOLOGY                                                                      6

 What is ETL – ETL Vs ELT – Types of Data warehouses - Data warehouse Design and Modeling - Delivery Process - Online Analytical Processing (OLAP) - Characteristics of OLAP - Online Transaction Processing (OLTP) Vs OLAP - OLAP operations- Types of OLAP- ROLAP Vs MOLAP Vs HOLAP. 

UNIT III META DATA, DATA MART AND PARTITION STRATEGY                       7 

Meta Data – Categories of Metadata – Role of Metadata – Metadata Repository – Challenges for Meta Management - Data Mart – Need of Data Mart- Cost Effective Data Mart- Designing Data Marts- Cost of Data Marts- Partitioning Strategy – Vertical partition – Normalization – Row Splitting – Horizontal Partition 

UNIT IV DIMENSIONAL MODELING AND SCHEMA                                               6 

Dimensional Modeling- Multi-Dimensional Data Modeling – Data Cube- Star Schema- Snowflake schema- Star Vs Snowflake schema- Fact constellation Schema- Schema Definition - Process Architecture- Types of Data Base Parallelism – Datawarehouse Tools  

UNIT V SYSTEM & PROCESS MANAGERS                                                                 6 

Data Warehousing System Managers: System Configuration Manager- System Scheduling Manager - System Event Manager - System Database Manager - System Backup Recovery Manager - Data Warehousing Process Managers: Load Manager – Warehouse Manager- Query Manager – Tuning – Testing 

                                                                                                                            30 PERIODS 

PRACTICAL EXERCISES:                                                                           30 PERIODS 

1. Data exploration and integration with WEKA 

2. Apply weka tool for data validation 

3. Plan the architecture for real time application 

4. Write the query for schema definition 

5. Design data ware house for real time applications 

6. Analyse the dimensional Modeling 

7. Case study using OLAP 

8. Case study using OTLP 

9. Implementation of warehouse testing. 

COURSE OUTCOMES: 

At the end of the course the students should be able to 

CO1: Design data warehouse architecture for various Problems 

CO2: Apply the OLAP Technology 

CO3: Analyse the partitioning strategy 

CO4: Critically analyze the differentiation of various schema for given problem 

CO5: Frame roles of process manager & system manager 

                                                                                                              TOTAL: 60 PERIODS 

TEXT BOOKS 

1. Alex Berson and Stephen J. Smith “Data Warehousing, Data Mining & OLAP”, Tata McGraw – Hill Edition, Thirteenth Reprint 2008. 

2. Ralph Kimball, “The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling”, Third edition, 2013. 

REFERENCES 

1. Paul Raj Ponniah, “Data warehousing fundamentals for IT Professionals”, 2012. 

2. K.P. Soman, ShyamDiwakar and V. Ajay “Insight into Data mining Theory and Practice”, Easter Economy Edition, Prentice Hall of India, 2006.