Explained: What is Databricks and why do we need it?

Before we understand as to what exactly is Databricks, we need to understand what is Apache Spark. Apache Spark is like a super-smart computer system that can handle lots and lots of information at the same time. It helps people do really big tasks, like sorting through a huge pile of data, figuring out patterns, and solving complex problems. Spark can also work with different kinds of jobs, like analyzing data in batches, processing data in real-time as it comes in, and even teaching computers to learn and make decisions. It’s like having a super-powered brain for data! Cool? Now lets understand Databricks! <img alt="" src="https://miro.medium.com/v2/resize:fit:700/0*fDVqOPYVb9PxbdmC.png" style="height:368px; width:700px" /> Source: <a href="http://databricks.com/" rel="noopener ugc nofollow" target="_blank">Databricks</a> So basically, Databricks is a cloud-based platform built on Apache Spark that provides a collaborative environment for big data processing and analytics. It offers an integrated workspace where data engineers, data scientists, and analysts can work together to leverage the power of Spark for various use cases. Databricks is important because it makes it easier to use a Apache Spark. Instead of having to worry about all the technical stuff behind the scenes, Databricks gives you a simple and friendly way to use Spark. It takes care of all the complicated setup and management stuff so that you can focus on working with your data and doing cool analytics tasks. It’s like having a magic helper that takes care of the boring stuff, so you can have more fun exploring and analyzing your data. <a href="https://medium.com/towards-data-engineering/explained-what-is-databricks-and-why-do-we-need-it-4391729612f8">Read More</a>