More cost-effective computing

A federal government agency accustomed to handling big data wanted to modernize its IT infrastructure and extend self-service analytics to its business users, so it turned to BNL Consulting and SAS®.

The agency processes several large surveys each year with annual, quarterly or monthly timetables and data sets that contain millions of records.

"A couple of performance issues had started to creep in, and the user interface was outdated,'' notes Robert Lill, President of BNL Consulting, a provider of business intelligence solutions primarily to large government and nonprofit agencies. "The organization needed a service-oriented architecture that would allow for growth and flexibility.''

BNL's work with this customer evolved from the agency's need for an enterprise architecture that no longer relied on green screens and lots of IT staff to maintain the code. The agency wanted to extend self-service with point-and-click data access as well as to improve interactive and batch survey processing.

SAS provides integration options that make it a hub in the hub-and-spoke architecture that a lot of government agencies are starting to build.

Robert Lill

The sensible approach

While the agency could have considered other options, it chose to maintain the core SAS functionality already in place and migrate to a more recent version of the software. Staff already knew how to use SAS and had built powerful backend processes for statistical computations that worked well.

BNL helped the agency migrate to more modern IT technology without losing any functionality and while maintaining the current processes, timelines and integrity of the survey processing itself.

"SAS has positioned itself well to integrate with a large enterprise. It can analyze large lines of data and has a very intuitive graphical mode,'' Lill says. "SAS provides integration options that make it a hub in the hub-and-spoke architecture that a lot of government agencies are starting to build.''

In choosing BNL, the agency sought a consulting partner that would help it work with the power of SAS independently.

"They didn't want to outsource it completely,'' Lill explains. "They wanted a partner that would assist in building it and training the staff so they could maintain the system themselves and wouldn't depend on outside vendors going forward.''

Fewer clicks, fewer boxes

In the past, analysts relied on developers to produce reports. This took a week or longer.

"Today, they can use the Web-based tool and with one click get information,'' Lill says. "This frees up developers to create more self-service options for business users."

Meanwhile, SAS Grid Computing helps the agency get the most from its hardware and speed up performance, ultimately saving money. It lets the agency create a managed, shared environment for processing large volumes of data and analytic programs quickly using dynamic, resource-based load balancing. SAS jobs can be split up and run in parallel across multiple symmetric multiprocessing (SMP) machines using shared physical storage. This allows IT to build and manage a lower-cost, flexible infrastructure that can scale to meet rapidly changing requirements.

An end to silos

While infrastructure modernization and analyst self-service were critical features, the agency was also taking a long-term view of the data.

"They wanted a flexible, extensible system where they can add more surveys to the system and integrate data from across the enterprise. They did not have that flexibility before,'' Lill says. "And providing an improved interface to analysts has other perks: They are more likely to detect errors and provide corrections for better data quality."


Modernize a legacy IT system, provide self-serve reporting and gain cost-effective computing for large analytic projects.



Greater productivity, better use of IT resources, faster reporting; increased processing power and scalability.

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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