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EMA Impact Brief
To Cloud, or Not to Cloud: Keys for Managing Your Advanced Analytics in a Hybrid Ecosystem
Date: 12/21/2017 Length: 7 pages Cost: $99.00

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Abstract:
Over the past twenty years, the concept of the cloud (technology implementations outside the traditional on-premises data center model), has taken an interesting path. Evolving from application and infrastructure hosting models to multitenant "as a service" architectures, organizations can now implement enterprise-grade technology environments without the level of effort and investment that a traditional data center would require.

As early as 1999, Salesforce.com changed how companies look at critical applications that reside completely outside a data centerís four walls. By targeting end-user stakeholders outside the core IT department in sales and marketing teams, Salesforce.com established the credentials for, and advantage of, externally-administered solutions. In 2006, Amazon launched its first services ready for primetime: Elastic Compute Cloud (EC2) and Simple Storage Service (S3).  With that beginning and the continuous flow of follow-up services, IT departments have changed their view the implementation of processing, storage, and data management.  

With this history of successful implementations spanning nearly two decades, the cloud has matured and can now be relied upon for many analytic use cases. From prototyping data warehouses and marts, to exploratory sandbox environments, to mission-critical applications, cloud-based analytics infrastructure is now on par with on-premises solutions for functionality, choice, and scale.

There are several aspects to consider when CIOs, CTOs, and their enterprise data architects decide "to cloud, or not to cloud" for their analytic ecosystems. The following infobrief provides executive guidance and debunks a few myths about the cloud.
Author:

John Myers


 




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