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 Course
Objective
One of the most dramatic new developments in database design
is the data warehouse, a powerful database model that significantly enhances managers'
abilities to quickly analyze large multidimensional data sets. In this course
students can learn practical information needed to design, manage, build and use
dimensional data warehouses for virtually any type of business application. Employing
many real-life case studies of data warehouses, the course provides clear guidelines
on how to model data and design data warehouses to support advanced multidimensional
decision support systems. Product-Oriented and Customer-Oriented data warehouse
examples are explored. Beginning with a simple grocery store data warehouse example
the course progresses to complex business applications in retail, manufacturing,
banking, insurance, subscriptions, and airline reservations.
What
will you learn
- How to design and build a data warehouse
- Migration to a data warehouse
- Life cycle of a data warehouse
- How the ETL Process works
- When transactional and when snapshot grains make sense
- How to build a value chain for the business
- How to get the most from star joins and standard data models
- How data marts and OLAP fit with data warehousing schemes
- What is Metadata
- What is Data Mining
- Data Warehousing Benchmarks
How
you will apply what you have learned
- Have a better grasp on Data Warehousing technology
- Understand how to model star-join schemas for various application
domains in Retail, Finance, Insurance and Shipments
- Understand the technology behind the buzz words associated
with Data Warehousing such as metadata, data mining, etc.
Who should attend
This course is for developers, managers, designers, data and database administrators and anyone interested in the field of building decision support applications.
Onsite Training Class Schedule
Registration
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