Analyst's Take: Teradata 12.0 Counters the Appliances - InformationWeek

InformationWeek is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Software // Information Management

Analyst's Take: Teradata 12.0 Counters the Appliances

More efficient processing, workload management and master data management help handle mixed workloads.

As organizations expand their business intelligence (BI) implementations to include operational users and processes, traditional approaches and technologies for BI are coming under pressure. Enterprise data warehouses must handle "mixed" workloads that include, along with standard analytic BI data, time-sensitive operational queries. According to recent benchmark research by Ventana Research, most operational workers need data to be updated at least once a day, and some users require more than one update an hour. This demand means that many organizations no longer can permit their data warehouses to manage a relatively static pool of data for a limited user community; the data stores must evolve to become enterprise hubs that manage a constant information flow to satisfy the requirements of a variety of users and business processes.

Few technology providers are more deeply involved in this shift than Teradata. Founded in 1979, the company has long been known for its focus on enterprise data warehousing and related analytic applications. Formerly a division of NCR, Teradata heads into 2008 as an independent, publicly traded company. Many Teradata customers are currently evaluating Enterprise Data Warehouse 12.0, an important release that provides technology for "active data warehousing," an expression the company coined in the late 1990s to describe how it addresses demand for operational BI and real-time analytics. Teradata also is adding to its information management portfolio technology for master data management (MDM) and workload management.


Operational BI and real-time analytics are important to companies in many industries. For example, in retailing, managers need to track daily inventories, take steps to improve the sales per customer and gain timely insight into the effectiveness of short-term promotions. To compete online, retailers need to analyze quickly whether to change prices based on current demand and inventory. They and other types of companies want to examine and analyze transactions as they occur to respond to problems in product availability and to be able to deliver focused cross-sell and up-sell offers. Additionally, managers want to see changes in business performance metrics as soon as possible so they can adjust sales and contact center processes and quotas based on what is happening now rather than on past forecasts.

Teradata's 12.0 release is intended to satisfy the need for enterprise data warehouses to support today's rapid pace of operational decision-making. One major challenge is to enable systems to load data continuously at the same time that they handle a large number of queries. Traditional data warehouses, which were not designed to address timeliness issues, separate these tasks by loading data in batch during off hours; in contrast, "active" operational data warehouses have to load data in the same time frame as they provide updates to users.

Enterprise Data Warehouse 12.0 addresses loading and related challenges to enabling immediate access to near real-time data. It offers faster internal database processing, which along with speeding up loading procedures should enable Teradata to support more diverse and numerous queries so that users see results more quickly. Competitively, improved processing allows customers to handle more workloads on existing systems rather than buying additional Teradata system nodes, a factor that has spurred customers' interest in data warehouse appliances. An important method that Teradata supports for improving performance is ELT — the extraction and loading of data into staging tables to speed up transformation — through its parallel database engine. Finally, offering another way to improve loading performance, Teradata has established a partnership with continuous availability specialist GoldenGate Software; with this technology, customers have the ability to capture data from non-Teradata databases such as Oracle and trickle-feed it into a Teradata enterprise data warehouse.

We welcome your comments on this topic on our social media channels, or [contact us directly] with questions about the site.
1 of 2
Comment  | 
Print  | 
More Insights
InformationWeek Is Getting an Upgrade!

Find out more about our plans to improve the look, functionality, and performance of the InformationWeek site in the coming months.

Remote Work Tops SF, NYC for Most High-Paying Job Openings
Jessica Davis, Senior Editor, Enterprise Apps,  7/20/2021
Blockchain Gets Real Across Industries
Lisa Morgan, Freelance Writer,  7/22/2021
Seeking a Competitive Edge vs. Chasing Savings in the Cloud
Joao-Pierre S. Ruth, Senior Writer,  7/19/2021
White Papers
Register for InformationWeek Newsletters
Current Issue
Monitoring Critical Cloud Workloads Report
In this report, our experts will discuss how to advance your ability to monitor critical workloads as they move about the various cloud platforms in your company.
Flash Poll