The Teradata Database channel includes discussions around advanced Teradata features such as high-performance parallel database technology, the optimizer, mixed workload management solutions, and other related technologies. Plus, you'll receive expert data warehouse training and the advice of the industry's most experienced data warehouse consulting professionals. You can submit Teradata Database Enhancement Requests here.

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Teradata Application Performance Tuning: Tips and Techniques

This session will discuss Application Query Tuning on the Teradata platform. 

Priority Scheduler in SLES 11 for Teradata Database 15.0

Join this in-depth presentation that covers the basic functionality of the SLES 11 Teradata Priority Scheduler.

Tables without a Primary Index

This session with provide information on the basic concepts of No Primary Index (NoPI) tables.

The Basics of Using JSON Data Types

This presentation provides the basics of using the JSON Data type including defining and using columns defined with them; using various functions and methods created for their usage; basic shredding and publishing functionality and usage with Array data.

Inside a Teradata Node

Alternate Title: Teradata 101. For anyone new to Teradata, this session is to acquaint you with the Teradata technology.

Hybrid Row/Column-stores: A General and Flexible Approach

Guest post by Dr. Daniel Abadi, March 6, 2015

Optimizing Disk IO and Memory for Big Data Vector Analysis

Optimizing Disk IO and Memory for Big Data Vector Analysis

Daniel Abadi  Nov 11, 2014  This is a guest post by Dr. Abadi   http://blogs.teradata.com/data-points/optimizing-disk-io-and-memory-for-big-data-vector-analysis/

Workload Management Capacity on Demand and other SLES11 Hard Limits

This session will explore the new options available for setting hard limits at different levels in the SLES11 priority hierarchy.

Explaining the EXPLAIN for Business Users

 

Whether you write your own code or it is generated for you, this is a topic that is essential for business users who run SQL queries.

Dealing with Natural Data Skew

Everyone is taught how to collect statistics in order to make Teradata queries run well but what if you've collected all the statistics that you can and you STILL have bad performance?

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