The journey to high-performance analytics
Organizations using a high-performance environment are seeing game-changing results
Rome was not built in a day. Similarly, high-performance analytics is a product of many cumulative architectural, computational and analytical advances. The ability to solve complex business problems by applying algorithms from multiple disciplines to increasingly larger volumes of data of all types – both structured and unstructured – is not a small task. It requires innovation at many levels and is the result of years of effort built on customer experience and a strong history of building robust enterprise-class products.
HIGH-PERFORMANCE ANALYTICS IN ACTION
For SAS, working with data and exploiting algorithms is built into our DNA. For more than 35 years, we've worked on innovative problems, and the size of data or the complexity of the analysis has never been a barrier. Every few years, we have tackled new challenges. Significant milestones in this journey have included:
In every one of these areas, the requirement to tackle larger problems and more complex scenarios continues to grow, which in turn requires our core analytical tools to grow – be re-invented – to satisfy these demands. At every level, we take advantage of multiple processors on a single machine as well as run on multiple nodes in a distributed environment.
These years of experience have taught us that the big data/big analytics problem must be addressed at many different levels. SAS' vision for high-performance analytics includes all aspects of "big": volume, velocity, variety and complexity. More importantly, when you think of high-performance analytics, you need to ensure it goes hand-in-hand with master data management and data governance as well.
"Our architectural breakthroughs make it possible for analytical developers to restructure their algorithms to exploit hardware advances and run in multiple distributed modes. "
The performance of an analytical algorithm alone is not sufficient to solve the entire business pain for an enterprise; pay attention to the performance of data movement as well.
SAS® High-Performance Analytics offerings are designed to provide fast execution and minimize data movement for both model creation and deployment. For example, the SAS Scoring Accelerator and SAS Analytics Accelerator provide scoring and modeling inside the database. Catalina Marketing has seen reductions in model-scoring time from 4.5 hours to around 60 seconds with this technology.
The next frontier
It allows us to provide a high-end, enterprise-class platform that combines in-memory analytics with a data platform that supports hardware failover and data replication, terabytes of storage, querying capabilities, ETL and many other capabilities that are important to IT and the end user. Our architectural breakthroughs make it possible for analytical developers to restructure their algorithms to exploit hardware advances and run in multiple distributed modes. This, I believe, is a key milestone for our overall development paradigm, which immediately opens a vast array of possibilities for us.
What does this mean for your business?
SAS Markdown Optimization analyzes three terabytes of historical sales data with multiple estimation and pricing algorithms targeted for this business problem. Using new SAS High-Performance Analytics technologies, the computation time was reduced from 30 hours to about two hours. This immense reduction in time allows the retailer to run more scenarios in the same window of time, providing the ability to look at alternate pricing strategies. Now, the retailer can provide the right prices to the right customers at the right time, in the end maximizing profit and clearing inventory.
What does this mean for SAS® software?
This story appears in the First Quarter 2012 issue of