How enterprises will use the cloud for big data analytics

Table of Contents

  1. Summary
  2. A majority of enterprises are interested in public cloud
  3. Security, privacy, and complexity are top enterprise concerns
  4. Key takeaways
  5. About Lynn Langit


Enterprise IT infrastructure largely predates the emergence of cloud computing as a viable choice for hosting data-driven applications. Large organizations are now showing real signs of adopting cloud computing for certain applications and a few forward-thinking enterprises are formulating the concept of data as a service, based on performing big-data analytics in the cloud. However, exactly when big-data analytics will move to the cloud remains an open question.

Compatibility, security, and performance concerns have kept enterprise organizations from being completely comfortable with the idea of moving their complex core applications to the cloud. Without a seamless application migration blueprint, the project can seem more like a headache — and a risk — than it’s worth. This report, which is based on a survey by Gigaom Research and sponsored by Cazena in September 2014, reviews the different considerations when moving some or all big data-analytics applications to the cloud. The report will give guidance to CxOs, IT and business leaders, and decision-makers at software-as-a-service (SaaS) companies and cloud service providers.

Key questions addressed in the report include:

  • Executives with an eye to costs are motivated to explore moving their data-intensive applications to the cloud. What are the primary drivers?
  • What types of cloud solutions are most prevalent now – public, private, government, or hybrid clouds?
  • What types of big-data workloads are best suited to the reality of what the vendors are providing currently?
  • How significant is the maturity of cloud-tooling in general, and of tooling around data-analytics projects specifically to adoption?
  • What are the primary blockers? Understanding security, privacy, and compliance needs are key components for ensuring that big-data analytics projects can be reliably migrated or newly hosted on the public cloud, but the complexities of vendor offers and of the current regulatory landscape are significant. Does the answer lie in education, legislation, or something else?


Thumbnail image courtesy: iStock/Thinkstock

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