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AI & Data Engineering

A collection of 53 issues

The Importance of a Good Data Model for Teradata Performance Optimization

Welcome to part two of our Teradata performance optimization series. In this article, we will delve into how a good data model can prevent future performance issues in data warehousing projects. We will also discuss the drawbacks of taking over operational systems' source definitions directly and th

Teradata Date Format and Time Values: Common Questions Answered

This article will address some common questions about formatting date and time values in Teradata. Teradata is a powerful relational database management system (RDBMS) that provides various functions to manipulate and manage date and time values. Understanding how to work with date and time data is essential for anyone using

Optimizing Join and Aggregation with Teradata UNION ALL Views

Teradata 16 introduces a new option for handling sets of rows combined with "UNION ALL" in views and derived tables, reducing resource usage. The optimizer can apply aggregation steps and join operations to each branch of the "UNION ALL" separately, resulting in smaller spool sizes and improved perf

Improvements in Tailoring Statistics Collection with Teradata 14.00: Using Sample, MaxValueLength, and MaxIntervals Options

Learn about the latest improvements in Teradata 14.00 that allow you to customize the collection of statistics to better suit your needs. These improvements include the option to set different sample sizes, consider more bytes for histogram creation, and choose the number of intervals for building s

Throttles in Teradata Workload Management: Usage, Request and Session Limits

What are Throttles used for in Teradata Workload Management? Throttles restrict concurrent sessions, requests, or utilities to safeguard vital resources, such as CPU, memory, and AMP worker tasks, from depletion. Their implementation in Teradata workload management minimizes contention for resources on highly concurrent systems, thus bolstering overall system performance. Throttling

Teradata Concurrency Control: Locking and Transactions Explained

Learn how Teradata Concurrency Control uses locking and transactions to prevent simultaneous updates, deletions, or insertions in different sessions.

Static and Dynamic SQL Characteristics: Examples and Differences

Learn about the characteristics of static and dynamic SQL in Teradata stored procedures. Discover how to use variables and parameters in SQL statements.

Teradata Partitioning: Row vs. Column for Efficient Data Access

Learn about Teradata Partitioning and how row and column partitioning can minimize data access resource usage. Read on for benefits and examples.

Teradata SQL Stored Procedures: Adding Procedural Functionality to Your RDBMS

Teradata SQL Stored Procedures enhance traditional SQL with procedural language features like iterations, condition and error handling, and variables. Learn more here.

Teradata Utilities: Fastload, Multiload, BTEQ, and TPump

Learn about Teradata's load utilities, which can be divided into two groups: those that bypass the transient journal and those that use it. Depending on your requirements, you may choose to load data either way. This article offers advice on how and when to use each tool, including BTEQ, TPump, Fast