While organizations store temporal data that is in effect over a period of time, efficiently querying that data to provide business insights can be a challenge.

Data Warehouses often contain data in effect for a time period, denoted by Start and End dates within a row. With time-period data comes a set of frequently asked business questions. For example, of home, auto, and life insurance policies, for what ranges of time have my customers 1) had zero policies active, or 2) at least one active, or 3) multiple active? Solutions to business questions of this type are not obvious using SQL. However, this session will show how to solve this class of problems efficiently with SQL instead of using stored procedures or exporting to another tool. See unique ways to apply correlated subqueries and the Ordered Analytical Functions SUM(), ROW_NUMBER(), and MIN() to this class of problems.

This course was designed for Data Analysts and Business Users of the Teradata Data Warehouse. It covers data distribution, access, storage and Teradata terminology and how to use the Teradata Utility SQL Assistant to submit Structured Query Language (SQL) statements. This course offers practical, hands-on experience with retrieving and manipulating data with Teradata SQL using both ANSI standard conventions and Teradata extensions to the language.

Offers training in advanced features & techniques used for retrieving & manipulating data with Teradata Structured Query Language (SQL) using both ANSI standard conventions & Teradata extensions to the language.

Offers practical, hands-on experience with retrieving & manipulating data with Teradata Structured Query Language (SQL) using both ANSI standard conventions & Teradata extensions.

Provides an overview of the Teradata Database architecture, as well as the features and benefits of the product. Teradata data distribution, access, storage and data protection methods are described. The suite of complementary load, access, and management utilities and tools are also covered, as well as Teradata Terminology.