Blogs
Dwaine Snow
OLTP and Data Warehouse Competitive Analyst
Dwaine has worked for IBM for the past 21 years. In that time he spent a number of years working on DB2 for Linux, UNIX, and Windows and has written 8 books and numerous articles on DB2, and has presented at conferences around the world. He recently started to work with our new colleagues from Netezza in the Product Management and Product Marketing arena, and is hoping to start writing his first Netezza book soon.
The Importance of Agility for Analytic Applications
April 20, 2012
In the context of data warehousing, agility means that the system can quickly and easily adapt to and accommodate; changes in data volumes, new data sources, new subject areas, new applications and/or new users. In order for a data warehouse to be able to do this, it needs to be able to run any query against any data model/schema. It must also be able to process all of the data, no mater what the query or what table(s) are being accessed, and do so quickly – without impacting the other users of the system.
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Customers move to Netezza in days, not months
February 3, 2012
A number of Teradata customers have moved some or all of their data and analytic applications to IBM Netezza data warehouse appliances. The reasons these customers give for their move invariably include:
Time to value
Agility and the ability to grow with new workloads
Reducing their cost of ongoing maintenance
Improving query performance – particularly for complex analytics and ad-hoc environments as data volumes grow.
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Not All In-Database Analytics Systems Are Created Equal
September 30, 2011
Co-Author: Matt Benati, Senior Director Product Marketing
Leading organizations differentiate themselves by analyzing massive amounts of interrelated data to predict business outcomes. High-volume, complex data analytics requires detailed data (not summaries) because influencing an individual’s actions requires that you track and analyze their unique interactions with your company. Traditional analytic systems and traditional databases cannot meet today’s need for predictive analytics on massive amounts of data.
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For data warehousing, “light-concurrency” means wait-times.
June 28, 2011
You might think this analogy is a little crazy when thinking about computers and computer software, but let me explain a little more.
In today’s global, dynamic environment, agile and pervasive analytics and business intelligence is critical to success. Whether you are a retailer who wants to cut shrinkage by finding employees that are using discarded receipts to do returns without merchandise, an insurance firm who wants to limit liability by not insuring too many properties within flood regions, a financial firm that wants to detect fraudulent charges quickly, or a line of business executive that wants to find all of the open opportunities in your territory, you want access to the information you need, when you need it. You do not want to have to wait in line behind everyone else in your organization just to run your query/report.
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