The preferred tooling for these projects are standard BI tools (55 percent) and analytic tools (49 percent).
"When you talk about why people want to move to the cloud and what they want to run in the cloud in terms of their big data applications, there is a lot of hype in the market about data science and data scientists and the ability of people to do predictive analytics," Moghe says. "When you ask people what workloads they want to run in the cloud and what's driving them to do big data in the cloud, the majority of the participants said they were really interested in exploring leveraging the cloud for their traditional analytics -- largely SQL-based. They want to leverage the cloud for their bread-and-butter analytics."
Despite the large percentage of enterprises that have either moved big data workloads to the public cloud or plan to do so, there are still significant barriers to adoption. Gigaom reports that security, privacy and complexity remain top enterprise concerns for data migration to the cloud. Fully 63 percent of respondents indicated security considerations where a key blocker for potential cloud-based implementations; 35 percent pointed to a lack of existing industry certifications (most commonly SOX or HIPAA); and 23 percent were concerned about the complexity of cloud and its impact on existing processes, tools and infrastructure.
Fifty-five percent of survey respondents say that "better understanding of the security posture of the cloud" would make them reassess their hesitation or refusal to implement analytic processes in the cloud.
"The key concern is transparency about public cloud vendor security and compliance practices," Langit says. "SOX and HIPPA are mentioned most often, but with an expressed need for more standards and understanding of how cloud vendors support these standards. Respondents appear to have a large amount of fear and confusion in this area and would welcome education about standards."
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