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Course Description

Advanced SQL Techniques for AnalystsHands-On Course

Course Objective

In-House Training for as few as 3 Attendees >>

Or Call Toll Free

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


A basic understanding of SQL and relational database system (RDBMS)


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