SAS has teamed up with Amazon to put its data analytics offerings in the cloud that it said would help customers decrease the time needed to analyse vast amounts of data.
The world’s largest privately owned software company said it would collaborate with AWS to "to help address the need for speed and flexibility in analysing large amounts of data quickly and for taking new analytic approaches".
“Cloud-based technologies allow businesses to do more with less at a time when being agile and effective is more critical than ever,” said Scott Van Valkenburgh, SAS senior director of Global Alliances.
Organisations will be able to use the SAS software to run big data and Hadoop projects on AWS. Among the products now available to use on AWS are SAS Data Management, SAS Business Intelligence and SAS Analytics.
SAS said its products will work with several Amazon services, including: Amazon Redshift, which will work with SAS as a data warehouse that customers can perform big data analysis; Amazon Elastic MapReduce, which in using Hadoop and SAS environments will allow customers to concentrate on data analysis rather than provisioning and administration; and AWS Test Drive, which will offer customers the ability to access SAS Visual Analytics to gain insights to support their business.
Anthony Volpe, chief corporate analytics officer at Lenovo said being able to run SAS on Amazon’s cloud infrastructure has allowed the firm to “democratise” analytics throughout its global operations.
“Not only do we reduce the costs associated with our own technology environment, but our customers also benefit because we can make critical decisions much faster by being able to analyse data from anywhere at any time. SAS in the cloud allows us to incorporate relevant changes into our business processes quickly and effectively, across our worldwide organisations.”
Dan Vesset, vice president of Business Analytics and Big Data Research at IDC said that deploying analytics within the cloud “gives a business the ability to use more than just existing in-house systems to manage and analyse their data."
