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Data Analytics using SQL


Duration: 2.0 days

Method: Instructor-led with hands-on exercises.

Price: $1125.00

Course Code: DA1010


Programmers, Analysts, Database Administrators, Data Scientist, IT Managers and anyone that performs analytics on data in a relational database using SQL. This is specific to data stored in a relational database such as Db2, Oracle, SQL Server or PostgreSQL.


Data is everywhere and lots of it. What do you do with so much data? How do you make sense of it? What SQL programming functions add value to your business data?This class shows you the technical side of providing data analytic output using SQL code and many of its analytical functions along with strategic thinking in solving business problems. It will show you how to highlights trends in data and pinpoint data outliers. You will learn to use many of the database SQL functions and logic techniques to help support data driven inquiries whether you are being asked to solve complicated problems or use many of the analytic and statistic functions that the SQL language provides. Come prepared to start building today's practical skill set that will help you build, understand and support data driven applications. We begin with an in-depth discussion of OLAP functions, and quickly move on to analytic and statistic functions. Within each topic you will learn how to code and then how to analyze the outputs. Each topic can be reinforced with hands-on workshops. Examples and workshops are provided for the following platforms with discussion of the relevant differences: Db2 for z/OS, Db2 for Linux, Unix & Windows, Oracle, SQL Server and PostgreSQL.


A basic understanding of Structured Query Language (SQL).


  • I. What is Data Analytics?
    • Data Analysis Discussion
    • Data Science Discussion
  • II. OLAP Functions & How They are Used in Analytics
    • Ranking and Aggregations related to analytics
    • Ranking and Trending Outputs
    • OLAP Moving Ranges
    • OLAP MOVING Rows Between vs Range Between
  • III. Percentiles
    • Top and Bottom Percentages of data
    • Cumulative Distribution of Values
    • Percent Ranking of Values
    • NTILE Function
    • LEAD and LAG Analytics
    • Outliers
  • IV. Statistic Functions
    • What do they mean, and how to use them
    • Mean, Median, Mode
    • Spread, Range
    • Variance, Standard Deviation
  • V. Advanced Grouping
    • Grouping Sets
    • SQL Rollup
    • SQL Cube