Engineering & Construction
Struggling with Managing Multi-Cloud Platforms? Experts Recommend Finding Horizontal Threads Across Your Data Ecosystem.
Organizations managing multiple cloud platforms can reduce complexity and costs by standardizing analytics across their fragmented data ecosystems
This story was produced through MarketScale. See how Engineering & Construction teams put it to work with Partner & Channel Enablement.
Key takeaways
Organizations managing multiple cloud platforms can reduce complexity and costs by standardizing analytics across their fragmented data ecosystems
Businesses utilizing multi-cloud platforms face significant challenges in efficiently extracting data and insights, as revealed in the SAS report "A Silver Lining from Every Cloud." The study surveyed over 200 decision-makers in the UK & Ireland and found that 70% of businesses use different analytics platforms for each cloud, leading to increased time consumption and costs. Additionally, the proliferation of multiple cloud platforms heightens cybersecurity risks. These findings underscore the importance of strategic cloud infrastructure investments to optimize data usage and security.
70% of businesses use different analytics platforms for each cloud, leading to increased time consumption and costs.
How have these challenges impacted companies' abilities to leverage data insights from their cloud platforms and make actionable decisions, and are there ways to navigate these complexities?
Steven Dickens, Vice President of the Futurum Group, believes there are challenges dealing with multi-cloud platforms, but solutions are available.
Steven's Thoughts
"When you factor in that data could be spread across a number of different cloud platforms, whether that's Microsoft Azure, Google Cloud Platform, or Oracle Cloud Infrastructure, the complexity and challenges really manifest for the enterprises we speak to.
Some of the key challenges we see from clients and enterprise vendors that we speak to are the ability to manage in a hybrid multi-cloud environment, whether that's at the application level, whether that's at the security level, whether that's at the DevOps level, or whether it's at the data level. Some of the challenges we see as organizers wrestle with how to manage data. Where do you back that data up, who has access to it, and how do you secure it while it's in use, in transit, and at rest? How do you provide fault tolerance and resilience across that data landscape?
All of those are key challenges that we're seeing. Then when you factor in that, that data could be spread across a number of different cloud platforms, whether that's Microsoft Azure, Google Cloud Platform, Oracle Cloud Infrastructure, or private cloud instances either in your own data center or in hosted data centers, the complexity and challenges really manifest for the enterprises we speak to, and they're wrestling with how they do that.
Some of the emerging approaches we're seeing are how do you look at some of these horizontal layers, so data fabrics, data layers, data platforms, also orchestration, DevOps platforms, how to provide some horizontal connective tissue across your multi-cloud environment to improve operational effectiveness, reduce cost and improve the speed of delivery for enterprises as they look to operate in a dynamic business landscape."
How do you provide some horizontal connective tissue across your multi-cloud environment to improve operational effectiveness, reduce cost and improve the speed of delivery for enterprises as they look to operate in a dynamic business landscape.
— Steven Dickens, Vice President of the Futurum Group
About the author
STEVEN DICKENS MISSION To work with organisations globally to provide thought leadership, content and advisory services so they can address the challenges and opportunities that a digital world presents. PRACTICE COVERAGE Public Cloud IaaS; AWS, Azure, GCP, OCI and IBM Cloud as well as public cloud connected compute such as Outpost, Satellite, Stack and Cloud-at-Customer, this focus also includes containers, K8S, Cloud-native orchestration & Virtualisation Operations Software; Log management, automation, observability, and console reporting. Servers & Compute including; x86, UNIX, Mainframe, HPC and Hyper-Converged infrastructure Open Source: Linux Operating systems and Open-Source tooling and operations software. Mainframe Ecosystem including hardware, software, service providers and outsourcers. WHO STEVEN WORK WITH With 25+ years of experience in cloud, hardware, services and software along across multiple industries, he engages with senior leaders in large organisations, new emerging vendors and the major Tech vendors to define strategy and provide engaging content and advisory services.
