Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge.
This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.