Teradata SQL Assistant - Advanced SQL Engine - Teradata Database

Database Introduction

Product
Advanced SQL Engine
Teradata Database
Release Number
17.05
17.00
Published
June 2020
Language
English (United States)
Last Update
2021-01-23
dita:mapPath
qia1556235689628.ditamap
dita:ditavalPath
lze1555437562152.ditaval
dita:id
B035-1091
lifecycle
previous
Product Category
Teradata Vantage™

Teradata SQL Assistant stores, retrieves, and manipulates data from Teradata Database (or any database that provides an ODBC interface). You can store the data on your desktop PC, and produce consolidated results or perform data analyses using tools such as Microsoft Excel. In addition to ODBC connectivity, Teradata SQL Assistant can connect to Teradata Database using .NET Data Provider for Teradata, which can be downloaded from the Teradata Corporation website.

The following table contains information about key features of Teradata SQL Assistant.

This feature… Allows you to…
Queries
  • Use SQL syntax examples to help compose your SQL statements.
  • Send statements to any ODBC database or the same statement to many different databases.
  • Limit data returned to prevent runaway execution of statements.
Reports
  • Create reports from any database that provides an ODBC interface.
  • Use an imported file to create many similar reports (query results or answer sets); for example, display the DDL (SQL) that was used to create a list of tables.
Data manipulation
  • Export data from the database to a file on a PC.
  • Import data from a PC file directly to the database.
  • Create a historical record of the submitted SQL with timings and status information, such as success or failure.
  • Use the Database Explorer Tree to easily view database objects.
Teradata Database stored procedures Use a procedure builder that gives you a list of valid statements for building the logic of a stored procedure, using Teradata Database syntax.

Teradata SQL Assistant electronically records your SQL activities with data source identification, timings, row counts, and notes. Having this historical data allows you to build a script of the SQL that produced the data. The script is useful for data mining.