CMDBID: 107447 | Course Code: WA1817 | Duration: 3 Days
This workshop focuses on the full end-to-end process of the data warehouse, namely, Gather, Store and Deliver.
Among the most important things you will learn at this workshop is how to design the overall process of the data warehouse. The seminar will teach how to effectively accomplish this, while ensuring a quality data warehouse design.
This course will cover five main areas:
What is unique about a Data Warehouse project?
What are valid different architectures or topologies for a data warehouse?
How do you design the Extract-Transform-Load (ETL) process?
What are the main considerations in designing the data structures?
How do you deliver productive BI tools and applications?
This is a workshop, not just lecture. Students will perform a number of exercises throughout the life cycle of the data warehouse to drive home complete understanding of the data warehouse development process and its issues.
Outline of Designing the Data Warehouse Workshop Training 1. Introduction to Data Warehousing
Scope and levels of modeling
Kinds of data
The framework for data modeling
Challenges in data management
Five major characteristics of data warehouse
Types and technologies of data warehousing
2. Data Warehouse Architectures
3. Data Warehouse Methodology
Explanation of methodology steps
Iterative nature of development
4. Information Gathering
5. Data Store Layer
Building the Data Warehouse Model
Levels of Data In the Enterprise
6. Modeling Time and History
Short term and long term view
Four ways of handling time and date
Capturing business changes
Importance of representing the business time dimension
7. ETL Layer
Defining transformation requirements
Defining transformation rules
The transformation requirements spreadsheet
Building transformation processes
Enforcing controls in the ETL process
Designing the transformation process
Complete coverage transformation types
Dealing with change data
Supporting surrogate keys
Near-real time transformation
8. BI Layer
Designing the BI interface
Matching the BI interface to the user
Types of BI technologies and design
Types of reporting
OLAP in all its forms:
Data sparsity and density
Data explosion due to calculations, rollups and summaries
9. Data Warehouse Technology
Categories of warehouse tools
Review of major products
10. Important Considerations and Issues
Denormalization and performance
Archiving and purging
Data distribution and replication
Alternative Models For Copied Data
11. Managing Data Warehouse Projects
Data warehouse project structure
Managing multiple data warehouse projects
Data distribution issues
12. Summary and Conclusion
Selected warehouse projects
Critical Success Factors
13. Case Studies
Complete group case study (moderately sized)
Complete individual case study (large)
14. Glossary 15. Explanatory Texts
Our clients have included prestigious national organisations such as Oxford University Press, multi-national private corporations such as JP Morgan and HSBC, as well
as public sector institutions such as the Department of Defence and the Department of Health.