Capgemini Intros Big Data Analytics Solution on Amazon Web Services
Capgemini, the provider of consulting, technology and outsourcing services, is partnering with Amazon on Elastic Analytics, a business intelligence (BI) and Big Data analytics solution available via Amazon Web Services (AWS).
According to Capgemini, the solution includes the infrastructure, management, security, support and maintenance needed to run analytics solutions on a cloud environment. Further, Elastic Analytics supports most popular BI software packages.
Scott Schlesinger, senior vice president for Business Information Management at Capgemini called AWS “a highly adaptable and extensible platform” that makes it relatively quick and easy to launch advanced analytics initiatives.
The solution can combine large source sets of structured and unstructured data, using existing ETL technologies and the AWS Hadoop-based solution, Amazon Elastic Map Reduce, to extract and merge the data into optimized analytics engines. Capgemini customers will then be able to leverage this environment to gain business insights from their data.
“Capgemini is enabling global enterprise organizations to rapidly scale out BI and Big Data solutions in the cloud, and we’re excited to be working closely together with them to bring these benefits to customers via AWS,” said Terry Wise, director, Worldwide Partner Ecosystem, AWS.
Capgemini clients already using the AWS cloud for their analytics efforts include a large life sciences company that used AWS to create a Competitive Intelligence portal for its executives and a U.S.-based telecommunications firm that used the AWS cloud to address data loading and performance problems that slowed its analytics reporting.
Drew Robb is a writer who has been writing about IT, engineering, and other topics. Originating from Scotland, he currently resides in Florida. Highly skilled in rapid prototyping innovative and reliable systems. He has been an editor and professional writer full-time for more than 20 years. He works as a freelancer at Enterprise Apps Today, CIO Insight and other IT publications. He is also an editor-in chief of an international engineering journal. He enjoys solving data problems and learning abstractions that will allow for better infrastructure.
