Learn how to make your Teradata Data Warehouse a virtual time machine!

Teradata Active System Management (TASM) continues to evolve to increasingly higher levels of automation and usability. Come hear what new TASM offerings are available in release 13.x, and how you can best leverage these new features.

Have you ever been bewildered trying to tune complex Teradata queries that go on for pages and pages of EXPLAIN text?  This presentation goes beyond "Explain the Explain", to teach strategies and techniques for quickly deciphering the most expensive operations in your queries.  Taught by a 20+ year Teradata veteran, examples of real queries gathered from some of the largest production environments in the world are used.  This is advanced material covered at a quick pace.

Does your data warehouse contain organizational hierarchies, bills-of-material, or transportation networks? If so, you likely have a good candidate business problem for recursive SQL...

This is more than an overview of the Indexes that are available in Teradata and how they work.

Statistics about tables, columns and indexes are a critical component in producing good query plans. This session will examine the differences between random AMP sampling, full statistics collection, and USING SAMPLE collection, and will share details about how each of these 3 approaches works internally.  Statistics histograms, their uses and limitations, will be explored.  You'll get some insights into collecting statistics on multiple columns, on indexes, on and on the system-derived column PARTITION.   Statistics extrapolation will be touched on briefly, and the session will wrap up with some general recommendations for collection statistics.

This session will focus on block-level compression (BLC), how it works, what compression rates you can expect, and where it is appropriate to define. Examples of the impact on CPU usage and elapsed time when queries access compressed tables will be shared, and the overhead while performing different database operations on these tables will be explored. Plenty of tips and techniques for successful use of BLC are offered.

This presentation will provide recommendations and guidelines for using leading practices to enable system and performance tuning.  You will learn the benefits of using Teradata's most recent set of recommendations to manage workloads on a Teradata system. For example, by using Teradata's data collection guidelines, recommendations for Account Management and Logging, a user will be able to identify, analyze and tune problem queries for better performance. This presentation will also focus on how to use the tools provided in the Teradata Analyst Pak. 

My batch is completing late, the tactical queries show inconsistent response times, some applications show extreme variability in resource consumption, the canaries are hoarse!
Bad queries need to be fixed! We will explain why certain queries are bad and visualize how they impact Teradata performance. We will show how to find them, discuss most common mistakes, and give tips on how to fix them. Techniques to measure 'incoming traffic' from highly volatile applications will be discussed.

Time is one of the most powerful dimensions a data warehouse can support. Unfortunately it’s also one of the most problematic. Unlike OLTP environments that focus on only the most current versions of reference data, DW environments are often required to present data not only as it currently exists, but also as it previously existed. Implemented correctly, a data warehouse can support several temporal orientations, the three most common being “current,” “point-in-time,” and “periodic.” Implemented incorrectly, you will create a solution that will be impossible to maintain or support.