Big Data and DevOps: The Case for Bringing Them Together

If you work with Big Data, you might not think DevOps has much to do with you – and vice versa. But you’d be wrong. Here’s why Big Data and DevOps make sense together.

You’ve probably heard of Big Data and data analytics – especially if you’re reading this blog. But if you work in the world of data, you might be only vaguely or not at all familiar with DevOps.

So, here’s a quick definition: DevOps is a philosophy of software development and delivery that emphasizes constant communication across the organization. It reflects an effort to streamline software production by removing the barriers that have traditionally separated developers from IT Ops teams and everyone in between.

An important concept that is closely related to DevOps is the idea of “continuous delivery” of software. Under the continuous delivery model, code is designed, written, tested and pushed into production environments on a constant basis.

DevOps makes continuous delivery possible because DevOps facilitates constant collaboration between all the different teams responsible for pushing software down the delivery pipeline – as opposed to traditional modes of software production, where long delays tended to occur whenever code was handed off from one team (such as the developers) to another (such as testers) and no one could work in parallel.

You’ll notice that the description of DevOps and continuous delivery didn’t mention data. And it’s true that, by most conventional definitions, DevOps is not closely linked to the field of data analytics.

But maybe it should be. If the goal of DevOps is to make software production and delivery more efficient, then including data specialists within the continuous delivery process can be a big boon for organizations working to embrace DevOps – which, by the way, is now a mainstream practice among even the largest enterprises, according to recent analysis.

After all, despite the exclusion of data analysts from traditional ways of thinking about DevOps, they have crucial contributions to make at all stages of the software delivery pipeline. By integrating Big Data and DevOps, organizations can achieve the following:

Most software interacts with data in some way. When you’re updating or redesigning an app, you want to have the most accurate understanding as possible of the types of data sources your app will be working with. And the sooner your developers have that understanding, the better.

For this reason, being able to collaborate with your data experts before programmers even start writing new code can help them to plan updates in the most effective way from a data perspective.

Data handling problems can be a big source of errors when software is being written and tested. And the more complex your application and the data it works with, the higher the chance of errors.