How Organizations Run Big Data Applications
in the Cloud

Executive Summary

This survey was conducted to better understand how organizations run their big data applications and workloads in the cloud. When IT doesn’t possess visibility into their big data system performance, overspending is almost guaranteed.

We wanted to learn how enterprises are thinking about their big data applications in the cloud, whether they are staying within budget, and what their strategies are for optimizing operations.

This survey was conducted online, in November of 2020, among 750 participants from a range of industries.

Key Findings:

For 64% of respondents, “cost management and containment” is their biggest concern when running cloud big data technologies and applications.

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For 1 in 12 respondents, cloud spend was expected to be over budget by 40% or more.

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For a majority of respondents, a desire to “better optimize current cloud resources” was their highest priority big data cloud initiative.

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In 2020, for 1 in 3 respondents, cloud spend was projected to be over budget by between 20% and 40%.

On Big Data in the Cloud Strategy

The majority of respondents cite cost management and containment and increased complexity as their biggest concerns when running big data applications in the cloud.

What do enterprises cite as their biggest concern when running applications in the cloud?

A. Shifting from CapEx to OpEx for cloud expenditures

B. Cost management and containment

C. Increased complexity and lack of expertise

D. Lack of control as the business units are spinning up their own instances

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On Big Data Cloud Initiatives

What Are Enterprises’ Top Big Data Cloud Initiatives?

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Using the mean score, the largest number of respondents identified optimizing current cloud resources as their top initiative. Their second priority was migrating workloads to the cloud.

Get the Cloud Survey Report

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IT operations teams can’t afford runaway costs and missed SLAs. Pepperdata makes sure cloud agility doesn’t lead to trouble by automatically optimizing big data cloud resources to reduce costs and track resource usage for clear accountability. Users get powerful insights while controlling costs and improving application performance to achieve their business requirements. In addition, users gain insight for planning, debugging, and troubleshooting, plus the confidence that their applications and workloads will meet SLAs.

Learn how you can start optimizing today.

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