Keep it Simple: Gaining Efficiency Through
Data Warehouse Appliances

Just a few years ago, there were not many companies with massive amounts of data to store and analyze. Now, almost everywhere you look, companies have to, want to, or plan to capture, retain, and eventually use vast amounts of data.

This has lead to the development of specialized storage appliances to handle data management requirements. The appliance approach relieved companies of having to build their own infrastructure out of a mix of iron, wiring, and hand-coded software modules. If companies then didn't have to worry about managing their data, more time could be spent on the content of the data - the information inside - that can actually bring more tangible value to the business.

The data warehouse appliance achieved that by packaging together everything needed to build a data warehouse to manage all of this data. Data warehouse appliances are now far simpler to install and maintain than a typical database server plus storage infrastructure that was previously pieced together. They're easier to get up and running, but is that enough? How hard is it to "personalize" them so that they can adjust easily to constantly changing requirements?

Why talk about personalization in the context of data warehousing? Personalization is the element that brings the data warehouse appliance to the next level of usefulness, or relevance to most businesses. Once you get a taste for the type of business insight you can gain from making use of your data, the more questions you want answered. Greater flexibility will translate into more demands for scalability, accommodating both complex analytics and routine reporting with everything in between, handling more people wanting to do a greater variety of things with more data.

To build flexibility into your data warehouse, you need to start streamlining change effects. The more minimal the impact of a change, the easier you can adapt to the next wave of business requirements. Taking the steps you'll need to bring your infrastructure forward, is now an affordable option you can't afford to ignore.

Learn about Data Warehouse Appliances

New! Using the Data Warehouse Appliance for Operational BI
Krish Krishnan discusses the role of the data warehouse appliance and operational BI.

New! TECHNOLOGY AND EVOLUTION: DATAUPIA AND DW 2.0
Bill Inmon gives an objective account of how data warehouses have become large and dependent on MPP. He emphasizes that the data warehouse appliance is the economical approach to bringing MPP in-house.

Building a Best-fit Data Warehouse: Why Understanding Physical Database Structures Matter
Do you ever blame your database for not delivering the BI capabilities you expect, or for failing to handle increased volumes gracefully? Perhaps it is not inherently the database's fault. Could it be an infrastructure problem? There may be a better way to match the database and your BI workloads.

Greening the Data Center
John O'Brien, CTO of Dataupia, explains how carbon footprints are calculated in the data center and discusses ways to tame these power-hungry machines.

IDC on Telco Data Value
This IDC white paper by Dan Vesset examines the challenges faced by the telecommunications industry in managing data for the purposes of decision support and recommends action items to be considered as part of overcoming these challenges.

IDC on Retail Data Value
As retailers look to optimize existing business processes to maximize revenue, decrease costs, and grow profits, those with the most relevant information are able to more quickly and more accurately make decisions about current trends and predict future events to capitalize on opportunities or mitigate risks. Dan Visset examines how access to the right level of data granularity at the right time with data warehousing solutions that provide optimal scalability and availability forms the core of any business analytics system.