Importance of Hybrid Cloud for Big Data and Analytics

by Dynamix Group Writer

IT leaders and their C-level business counterparts are focusing on shifting and expanding their existing workloads to the cloud or building new workloads and integrating it with the pre-existing data for strategic purposes. However, many organizations remain skeptical about cloud data migration due to privacy and data security. The kind of data handled by corporations and used in their day-to-day functioning justifies the concern of transporting all their data on a public cloud. Thanks to the advancement in technology and cloud services, businesses can deploy a hybrid cloud, especially in the field of big data and analytics.

What is a Hybrid Cloud?

A hybrid cloud can be defined as ‘a cloud deployment using at least two different cloud deployment models.’ The deployment models may include IaaS, PaaS, or XaaS. It is a combination of on-premises and local cloud resources, which are integrated with one or more dedicated cloud and one or more public clouds. The combination of these two clouds is known as a “private environment.” The two are structured in a manner that they operate individually but remain connected on a private or public network.

A hybrid cloud may be owned, operated, and managed either by a third-party or the organization itself. It can be located on-premises or off-premises to function properly.

Why Hybrid Cloud for Big Data and Analytics?

A hybrid cloud allows various people to work with data and analytics capabilities. It also helps identify the areas and requirements where data capabilities and analytics should be placed in the hybrid cloud environment. Corporations need to consider where the data needs to be stored and the location of the analytical processing relative to the data. Following this, the first step for any analytics project should be to verify the external capabilities available in the public cloud and their location.

Other factors that impact the location of the data are legal and regulatory requirements. This is because of the data sovereignty laws in many countries that secure information about individuals, finances, and intellectual property from getting out of the borders. Where the processing will occur depends on the multiple centers of gravity of the systems.

Keeping all these aspects in mind, many corporations are taking a step forward towards cloud migration. In a more advanced scenario, transformations, including Teradata to Azure migration, have also been considered by the businesses, leading their way with respect to time and cost-efficiency.