How Your IT Organization Can Deliver Next-Generation Analytics
Gain business agility through architectural flexibility
" We've been helping our clients reach the right people with the right messages for 25 years, but with the predictive capabilities we have with SAS, we're able to do it with more precision than anyone else in the market."
Executive Vice President and CIO (retired)
Designing a robust, flexible analytical infrastructure is instrumental to achieving analytic success – and this responsibility falls squarely upon the shoulders of IT.
IT is tasked with developing an infrastructure that can support the various requirements for analytics, including reliability, performance and scalability. CIOs must be aware of enterprise architecture standards and specifications that can scale with growth, adhere to global standards and meet local requirements.
How SAS Can Help
Success comes from having access to the right tools, the right people and the right advice. At SAS, we understand that success is not limited to the quality of the technology but also the way the technology is used. Technologies and strategies you will need to succeed are:
- An integrated, enterprise analytical framework. SAS can help you develop an enterprise analytical framework that encompasses data access services, appropriate data marts, an enterprise data warehouse and integrated analytical disciplines so that value from cross-departmental analytic efforts can be shared, operationalized and optimized. The analytics and data warehouse environment should NOT be designed in a solo fashion. Rather, the environment should be comprehensive, integrated, built for the future, and easy to maintain and manage.
- High-performance analytics. Increasing the numbers and types of models that are available for creating predictive insights can improve the quality of analytical results. High-performance analytics from SAS enable your analytical teams to move from using simplistic to more advanced models, and to use more granular data for analysis rather than small samples. Models run in a fraction of the time with more complete data, enabling analysts to experiment more thoroughly and produce better answers in time frames not previously possible.
- Analytic lifecycle management. SAS will help you involve multiple teams and analytic disciplines so you can manage the analytics life cycle across your organization. From data acquisition to sandbox-style model development to production deployment and continuous feedback loops into operational data, SAS can help you move beyond a limited, project-based approach to tame the entire business analytics life cycle.
- Deployment diversity. Business agility requires architectural flexibility. SAS provides numerous deployment options, ranging from on-premise applications and cloud deployments to support for data warehouse appliances and mobile apps. We work with varying architecture topologies and an array of hardware vendors to support SMP, MPP and grid implementations so you can get the best ROI on your infrastructure investments.
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