451 Research's Alliance surveys provide evidence that analytic workloads are moving to the cloud faster than the database and data-warehousing platforms that have traditionally supported them.
As a growing volume of data originates and is stored in the cloud, there are an increasing number of options for enterprises to analyze that data where it resides.
There are also a number of cloud-based integration offerings that enable enterprises to combine cloud data with other data sources for analysis - without ever hitting on-premises server infrastructure.
From On-Premises to the Cloud
While analytics and data warehousing have previously gone hand in hand, the big-data trend has encouraged enterprises to process and analyze data that was previously ignored (data that resides in cloud-storage services that was never imported into a data warehouse).
This trend will continue because of the many advantages of analyzing data in cloud storage. In addition, SaaS and cloud-service providers are enhancing functionality for native analytics.
This means that there will be greater demand over time to migrate data analytics workloads to the cloud.
Separation of Compute and Storage
Traditionally, data analytics and business intelligence (BI) projects have relied on enterprise-data warehouses - centralized, on-premises platforms that integrate data from multiple applications and make it available for analysis.
Data warehouses combine compute and storage in a monolithic platform to meet performance requirements and to create a single view of enterprise data.
However, enterprises are increasingly taking an alternative approach: rather than bringing all the data together in one place for analysis, they are taking the analytic workloads to the data.
Workloads Moving to the Cloud
Data in the cloud is growing. A recent 451 Alliance storage study showed that 33% of 1,040 IT and storage-management professionals already used third-party cloud-storage services, and another 23% planned to purchase third-party cloud-storage services in the next 90 days.
The study also shows that the cloud is a growing location for storing data related to analytics workloads. And those workloads are moving to the cloud faster than the database and data-warehousing platforms.
As shown in the following chart, 4% of the respondents use public-cloud infrastructure (IaaS and PaaS) as the primary storage location for database and data-warehousing workloads, a figure that is expected to rise to 15% in 2018.
In comparison, 9% of respondents use public cloud infrastructure as the primary storage location for data analytics and BI workloads, and that number is expected to increase to 22% in two years.
Meanwhile, 23% of respondents use public cloud infrastructure as the primary storage location for big-data workloads today, a figure that is expected to jump to 40% in 2018.
The separation of compute and storage is driving analytics into the cloud. Enterprises are seeking new cloud-based approaches to analyze data where it resides, rather than bringing it on-premises for analysis.
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