Big Data and DevOps: Why They Are Better Together on A Project

published 27.07.2020 02:00

Why Big Data Needs DevOps While defining Big Data above, we mentioned that projects of this kind can be challenging in terms of: Handling large amounts of complex data Delivering the project faster in order to stay competitive on the market Responding to changes very quickly Without DevOps practices, it’s hard to resolve.

This makes it clear why Big Data companies more and more often rely on DevOps practices and involve data specialists in the CI/CD processes.

The Software Works According to The Expectations Data specialists, when closely involved in collaboration with other experts, help them understand the specifics of real-world data that software is going to deal with.

Data-Related Processes Are Streamlined Combining DevOps and Big Data helps streamline time-consuming processes such as data migration or translation, as well as improve the data quality.

Continuous Analytics Is Provided Your project will benefit from another useful DevOps practice such as continuous analytics, which streamlines the processes of analyzing the data and automates them via algorithms.

by Nadine Nykolaichuk from

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