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 Course
Objective
Making business intelligence accessible across the enterprise
is becoming increasingly important for organizations to achieve their strategic
goals. This has put a lot of pressure on database professionals to
a. Design robust and scalable database solutions to satisfy growing business
needs
b. Improve performance of their existing decision support systems
c. Build new enterprise data warehouses; integrating disparate data models from
enterprise systems like ERPs, CRMs etc
d. Implement reporting, OLAP and data
mining solutions with complex analytical requirements The success
of these database implementations heavily relies on the optimum use of underlying
SQL. This four day, lab-based, hands-on course, will introduce students
to the use of highly sophisticated SQL algorithms to solve real-world business
problems. What
will you learn - Identify practical uses of outer join, self joins
and co-related sub queries and when not to use them
- Use encoded characteristics
functions to gain performance
- Utilize subsets and sequences in analyzing
stock market like scenarios
- Understand techniques of cumulative and sliding
aggregates for data warehousing
- Understand what are statistical and financial
medians and how to implement them using SQL
- Mark causes of performance
problem in a given SQL query and rectify it using optimizer and in some cases
purposely not using the optimizer
- Real life uses of Table pivoting and
folding in reporting
- Handle Arrays, matrices, Trees and Graphs in SQL
- Implement
support structures that make algorithms easy for Extraction, Transform and Load
(ETL) operations
Who
should attend - Database designers, administrators, and application
programmers
- System analysts, Data warehouse architects
- Technical
support professionals
- End user reporting application programmers
Prerequisites
A basic understanding of SQL and relational database system (RDBMS)
Onsite Training Class Schedule
Registration
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