Containerization and AI for Data Analytics

Education Technology Insights | Wednesday, January 23, 2019

Containerization is a type of virtualization strategy which involves creating virtual pieces of hardware infrastructure and the operating system is shared by different containers. It emerged as a solution to mobile security problems for multi-use phones or mobile devices to bring your own device trends. Containerization could work to wall off critical business data on a multi-use phone. Combining containerization with artificial intelligence (AI) can hold the promise of transforming both static and dynamic security measures to reduce organizational risk exposure.

Analytical exploration is the key to an organization's ability for constant innovation, empowering best business context and taking the lead. The traditional approach of data and business analytics is no longer acceptable because it takes too long and runs the risk of removing possible insights before the business users access it.

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 Enabling the business with self-service data preparation will enable operation at the speed of business across the entire data value chain. Assisting the non-technical business user with intelligent guiding is also critical. The expected trends fulfilling the above requirements are

1. Containerization powered by Kubernetes: Kubernetes will take containerization to the next level with extremely scalable container distribution and management. Today's analytical workload cannot be contained in a single location. They need to be built in such a manner that they can be deployed to any location, run for as long as needed, and allocate resources upon completion. Kubernetes is the key factor for the swiftness, as it opens for users to provide zero administrative workloads deployed across multiple clouds where processing is available.

2. Embedded AI making data pipelines more intelligent:  Using AI organization can better understand the ingested data and how it can be better enriched with additional data elements. A key trend will be to deploy the algorithm to assist with every step of the data value chain. That is from ingesting to understanding the data.

Containerization of AI will become crucial for data analysis in unlocking breakthrough insights that will deliver great benefits for the business.

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