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Cloud Data Engineering

Humans evolved from the stone ages, to a much civilized current-day scenario. Likewise, computing has evolved. Gone are the days where applications ran on individual PC’s and hard drives. Fast-forward to now, computation and data storage is moved to a centralized system, the cloud- with everything residing on remote servers across the Internet. This gives us a means to get applications and data from any corner of the world, with a basic requirement of an Internet-connected machine.

Cloud computing requires a computing platform that exists in the cloud, on which these remote apps can run. A number of cloud platforms are available from different vendors, including Amazon, IBM, and Google, among others.


Why move from a traditional Data engineering system to Cloud ?

Fast-paced technology changes and ever-growing internet media, producing a-lot of data (millions of petabytes) is advocating the need to move to the cloud. Cloud offers scalability like no other hardware service can provide. With pay as you go features and complete automated pipelines, you can set-up your workflows in a very simple and easy way if you learn to master the craft.

Hybrid solutions for seamless cloud connectivity and datacenters to the Cloud provide a consistent platform which facilities easy mobility between on-premises and the public Cloud. Many vendors provide Security Development Lifecycle (SDL) which is an industry leading assurance process. It comprises security at its core and private data and services stay secured and protected while they are on Cloud.

How Crossroad Elf can be of assistance ?

It is a very important decision for enterprises to make, to select the right cloud vendor. Many offer hybrid solutions and an array of other beneficial features, which are important for any Cloud strategy today. Numerous enterprises have witnessed accelerated business growth by migrating to Cloud.

Crossroad Elf is a fast growing Software Development Company. We specialize in delivering high quality services in Data Analytics, Data Engineering, Data Science and Data Migration.

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