* Learn evolution of
decision support systems to data warehouse.
* See data mining.
* Understand how to populate the data warehouse.
* Learn Data Warehouse development life cycle.
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This
two-day seminar is designed to give the student a firm conceptual
understanding of the goals and techniques that are used in data
warehousing. The seminar explains the concepts and techniques in
plain English, and strips away all of the marketing hype to give
the student a clear understanding of how to construct a data
warehouse using the new technologies. The seminar begins with a
historical review of data warehousing and explains the basic
construction techniques for data warehousing and contrasts them
with traditional online teleprocessing systems.
Via
numerous in-class exercises, the student will leave this seminar
with an understanding of data warehouse design techniques for
relational databases, including STAR schema design, the
pre-aggregation of data, and online analytical processing (OLAP).
In addition, the student will understand multidimensional
databases, and be able to understand how they are created and
maintained.
This
seminar also introduces data warehouse "front-ends" for relational
OLTP engines and explains how these tools are used in real-world
situations. Lastly, the student is exposed to the data warehouse
development life cycle where they will understand data extraction,
data cleansing, metadata repositories, and practical tips for
insuring a successful warehouse project.
This course is designed for the working
Oracle professional and the amount of previous experience with
Oracle is incidental. Previous experience with relational
database management and SQL is helpful, but this class is
self-contained and has no formal prerequisites.
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