In 2022, big data analytics is essential to understanding the cloud. Given today's high computing demand and the potential for data generation that is more scalable, the acquisition and storage of data acquisition are critical concerns. Cloud storage can happen on easy-to-use platforms, and the technology is becoming increasingly essential for business stakeholders looking to access analytics-powered data. As organizations move toward Big Data as a Service (BDaaS), cloud-based big data analytics will tackle issues of scale, speed, and cost.

Due to the high demand for data, the existing systems require new technologies to handle large volumes of data. There remains a need to migrate from legacy systems to newer systems, like the cloud. Cloud migration benefits maintenance costs, accessibility to critical data, distributed architecture, scalability, and cycle times. Typically, data migration is driven by a need for the following: server and storage equipment replacements or upgrades; website consolidation; server maintenance; and data center relocation. The migration of existing data and big data workloads is not a straightforward process and contains challenges that must be anticipated.

Big data implementation

The big data revolution began in 2010. It evolved alongside smartphones, GPS sensors, the cloud, and, more recently, the Internet of Things (IoT).

Below are some of the reasons why big data implementations have increased in the last decade:

• The Hadoop ecosystem was developed to transform large amounts of structured, unstructured, and semi-structured data with commodity hardware — all of which is impossible with a relational database management system (RDBMS).
• There was a need to create an infrastructure that could be scaled horizontally.
• Hadoop rose to prominence in an era when the cloud had a minimal presence.

Many existing customers run Hadoop clusters on-premises to handle their big data workloads. These clusters require continual monitoring and maintenance to ensure quality performance.

Running services on the cloud can improve many of these tasks and offload responsibility to the third party hosting the services.

This is where Virtusa and Microsoft bring Azure Cloud Services to better enable big data workloads. Read this whitepaper to learn more about Big Data Analytics Migration to Azure Cloud Services- why it's necessary, how to accomplish it, and which Azure-provided services will enhance your migration solution.