Becoming a data-driven organisation in a world of exponential data growth could prove challenging and costly for most organisations. But hybrid cloud infrastructure offers the solution to future-proof analytics capability.
Moving to the cloud is no longer a question of ‘if’, but more about ‘when, what and how?’ Having started with low-risk data analytical applications and low-hanging fruit, businesses are now moving more and more workloads to the cloud for agility and scale.
At the same time, companies in almost every industry are on a quest to become completely data-driven. Therefore, it is not enough to move only IT services and technology infrastructure to the cloud: to be truly data-driven, companies need to be able to analyse their data, wherever it may reside – on-premises or across multi-cloud environments.
In a report, research company 451 Research highlights the following:
- 57% of enterprises are moving towards a hybrid cloud IT environment that leverages both on-premises systems and off-premises cloud/hosted resources in an integrated fashion.
- While more enterprises are focused on becoming data-driven, more than half their data today is “dark data” that is not being used for business insight.
However, Gartner notes data and analytics activities now extend to the edge, across distributed devices, servers or gateways located outside data centres and public cloud infrastructure. Analysts estimate that by 2025, more than 50% of enterprise-critical data will be created and processed outside the data centre or cloud.
Going hybrid
The intersection of hybrid cloud and data analytics should be a hybrid cloud analytics strategy underpinned by hybrid data warehousing or data lake technology, which will enable enterprises to support analysis of data where it resides − on-premises or in the cloud.
Because they are so scalable, cloud environments are particularly appropriate for analytics involving massive volumes of data. They put less strain on on-premises systems, potentially at a lower cost.
Because they are so scalable, cloud environments are particularly appropriate for analytics involving massive volumes of data.
One client, a major online betting operator, processes between 200 million and 600 million records per day. Simply reporting on the day’s records took four or five hours a day using on-premises servers. Adding further analytics capabilities on-premises would put significant strain on systems and risk causing poor performance and downtime.
The organisation is now moving to a cloud environment, which will slash the time to compile reports, and the organisation will also be positioned to carry out more detailed analytics to support further innovation and growth.
Another client, a mid-sized manufacturer, has moved to a cloud environment to run analytics for better stock loss management. The company’s on-premises infrastructure was not up to the demands of ongoing analytics, but a scalable cloud environment will allow it to gain insights to reduce losses and improve profits.
Consider this
There are some important factors to consider before moving to a cloud-based or hybrid cloud analytics model: for one, data volumes are exploding, making it important to consider what data and how much of it will be hosted and processed in the cloud.
Organisations should determine what workloads existing systems manage, and whether analytics would put strain on them. If on-premises infrastructure is not up to the task, organisations should consider which workloads should be moved to which clouds, and how they will be integrated.
For high-speed data processing in the cloud, organisations will need to link multiple streams of data from different sources, such as the ERP, CRM and HR payroll systems, and big data platforms like Hadoop and Cloudera.
They should also consider stakeholder concerns around security and data sovereignty. Should these be a key priority, they should look to running on a private cloud, or in a public cloud with localised data centres, such as AWS or Azure.
Another factor to bear in mind is that poorly-considered cloud migrations can prove costly, and costs can run away with you if not properly controlled. It is important to set limits and governance rules to ensure cloud use doesn’t scale over.
With a carefully-planned strategy, analytics in a hybrid cloud environment can deliver significant value and a faster ROI. Because the cloud is agile and scalable, environments can be spun up and down as needed, meaning organisations will always have access to sufficient capacity, with no wasted Capex and no risk to daily operations.
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