Agos Ducato processes big data 30 percent faster with SAS® Grid Computing
When Italian lender Agos acquired rival Ducato, executives faced far more than a corporate merger. They had to deal with an IT merger so vast that, in effect, it doubled the amount of data they had to manage. By implementing SAS Grid Computing, however, Agos Ducato improved performance and processing speeds by 30 percent.
With more than 2,000 employees, Agos Ducato sells its financial products via 200 branches and agencies, 30,000 contracted sales outlets and the networks of two major banking groups, Cassa di risparmio di Parma e Piacenza and Banco Popolare.
Increased performance levels, reduced processing time
At the same time, it needed a system with the flexibility and scalability to support future possibilities.
"Following the merger with Ducato, we ended up having to manage a doubled volume of data with obvious repercussions on response times and on data-warehouse upgrade performance," says Paolo Trincianti, Agos Ducato's CIO. "We therefore decided to start a renovation project based on high-performance analytics from SAS."
Rather than spend more on an infrastructure based on separate departmental systems, Agos Ducato implemented SAS Grid Computing, the component of high-performance analytics from SAS that provides a centrally managed computing environment for workload balancing, high availability and faster processing.
"To contain increases in [IT] management costs," says Trincianti, "we switched from a departmental platform, whose performance levels were related to the calculation capacities of a sole system that was expensive and not very modular, to a more scalable grid-computing architecture with theoretically infinite processing potential. This allowed us to immediately reduce the hardware investment required and to rationalize the management costs."
More than 80 users have direct access to the system, allowing them to run their own marketing, financial or risk analyses. With the new SAS platform, system performance is up 30 percent. And data processing times are down 30 percent with peaks of up to 80-90 percent.
Operating and application risks
"When we chose the SAS grid architecture," says Trincianti, "there were no comparable operating references in Italy. To achieve the expected results, it was necessary to re-engineer our application code for parallel execution on the nodes of the [grid-based] architecture. These conditions classified the project as 'high risk.' Despite this, after the analysis of the pros and cons and thanks to the guarantees offered by the SAS Italy team, we decided to proceed. And the facts now more than back up this decision."
According to Trincianti, SAS will support the design and development of new and more complex algorithms for marketing and risk as well as for measuring performance levels, promising greater efficiency and speed.
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.
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Handle processing requirements of big data to support business need for immediate answers
SAS® Grid Computing
System performance up by 30 percent; processing speeds improved an average of 30 percent, with peaks of 80-90 percent
“[SAS Grid Computing] allowed us to immediately reduce the hardware investment required and to rationalize the management costs.”