IBM Netezza Empowers Organizations to Make Data-Driven Decisions

Customers choose IBM Netezza data warehousing appliances for all kinds of reasons—and IBM Business Partners can play a pivotal role in helping them make the most of their investment. For example, business analytics software provider Aperity works with clients in the consumer packaged goods industry that often have difficulty forecasting future sales, especially in turbulent economic climates. These customers frequently make merchandising and operational decisions that are based largely on intuition.

To help its clients make more informed, data-driven business decisions, Aperity needed a data warehouse that could be fast, accurate, and cost-effective. Aperity teamed with IBM Netezza and IBM Business Partner Fuzzy Logix to develop its groundbreaking iSales Brand Management tool—a purpose-built, high-performance data warehouse appliance that makes advanced analytics on very large data volumes simpler, faster and more accessible.

By implementing the IBM Netezza data warehouse appliance, Aperity has achieved its goal of having a query response time of 20 seconds or less and can run complex analyses, with very little system maintenance. Combining the IBM Netezza data warehouse appliance with Fuzzy Logix’s in-database analytics enables Aperity to extend its iSalesBrandManagement to deliver accurate forecasts on more than 500,000 stores in minutes.

Kelley Blue Book solved a similar forecasting challenge with IBM Netezza. The company has long provided a reliable mechanism for buying and selling cars—and today, it is rapidly becoming an analytics-driven information powerhouse.

However, when advertising data volumes exceeded the capability of its existing SQL Server environment and the company needed greater computational power to estimate advertising inventory availability a year in advance, IT leaders turned to IBM Business Partners MicroStrategy and SAS to deploy an IBM Netezza data warehouse appliance that supports the company’s analytics requirements. The initial deployment was completed in just two days.

“With Netezza, we’re able to process all of our forecast models in a day, compared with the previous three to four days,” says Dan Ingle, Vice President of Analytic Insights at Kelley Blue Book. “This enables us to produce vehicle values that we can deliver in near real-time to the marketplace instead of waiting up to two weeks to push those values out to KBB.com.”

Netezza is helping organizations in the academic sector fulfill their missions as well. When researchers at the State University of New York (SUNY) at Buffalo—one of the leading multiple sclerosis (MS) research centers in the world—were investigating ways to slow the progression of multiple sclerosis (MS), they turned to big data. There are more than 2,000 genetic and environmental factors that may contribute to MS symptoms, so pinpointing which ones are the most influential is like searching for a needle in a haystack. By quickly building models using a range of variable types and running them in a high-performing environment, the research team hoped to gain insight into what causes the disease to progress in the body.

Today, the team uses Revolution R Enterprise for IBM Netezza in conjunction with the IBM Netezza analytics appliance to dramatically simplify and speed up very complex analysis on large data sets. The solution helped the SUNY Buffalo researchers consolidate all reporting and analysis in one location to improve the efficiency, sophistication, and impact of their research. As a result, the team can now conduct analysis in 11.7 minutes—down from 27.2 hours—and little to no database administration is required.

“There are lots of good reasons to use Revolution Analytics in an analytics appliance supercomputer like Netezza,” says Dr. Murali Ramanathan, University at Buffalo, State University of New York. “It’s faster and easier to program. It will speed up our computation. And, we have more data sets available to us because of how flexible and quick Revolution Analytics makes it to add and delete variables in our model.”

How has an IBM Netezza data warehousing appliance or an IBM Business Partner helped to transform your organization? Let us know in the comments!

Learn more

For more details on the SUNY Buffalo solution, read the press release or download the full case study here.

For more details on the Aperity solution, download the full case study here.

For more details on the Kelley Blue Book solution, download the full case study here.