#Databrick

#Databrick 

What is Databricks?

DataBricks is an organization and big data processing platform founded by the creators of Apache Spark. DataBricks was founded to provide an alternative to the MapReduce system and provides a just-in-time cloud-based platform for big data processing clients.

DataBricks was created for data scientists, engineers and analysts to help users integrate the fields of data science, engineering and the business behind them across the machine learning lifecycle. This integration helps to ease the processes from data preparation to experimentation and machine learning application deployment.

According to the company, the DataBricks platform is a hundred times faster than the open source Apache Spark. By unifying the pipeline involved with developing machine learning tools, DataBricks is said to accelerate development and innovation and increase security. Data processing clusters can be configured and deployed with just a few clicks. The platform includes varied built-in data visualization features to graph data.

Databricks develops a web-based platform for working with Spark which provides automated cluster management and IPython-style notebooks.

How is it being used?

Databricks is being used by enterprises from a wide variety of verticals, including financial services, healthcare, retail, media & entertainment, and utilities etc. Customers utilize databricks platform for a broad spectrum of use cases including core ETL, data discovery and exploration, data warehousing, data product deployment, and insight publishing using dashboards for internal and external audiences.

What problem does Databricks solve?

The business knows that there’s gold in all that data. Being a detective with a bunch of clunky tools and difficult to setup infrastructure is hard. You want to be the hero who figures out what’s going on with the business, but you’re spending all your time wrestling with the tools.

Databricks made big data simple. Apache Spark™ made a big step towards achieving this mission by providing a unified framework for building data pipelines. Databricks takes this further by providing a zero-management cloud platform built around Spark that delivers

1) Fully managed Spark clusters,

2) An interactive workspace for exploration and visualization,

3) a production pipeline scheduler, and

4) a platform for powering your favorite Spark-based applications. So instead of tackling data headaches, you can finally focus on finding answers that make an immediate impact on your business.

Who should use Databricks?

Anyone who wants to extract value from their big data quickly and efficiently ranging from data scientists and engineers to developers and data analysts. By providing an interactive workspace the exposes Spark’s native R, Scala, Python and SQL interfaces; a REST API for remote programmatic access; the ability to execute arbitrary Spark jobs developed offline; and seamless support for 3rd party applications such as BI and domain-specific tools; Databricks enables users to consume data and insights through the interface they’re most comfortable with.

Benefits

• Unlimited clusters that can scale to any size

• Job scheduler to execute jobs for production pipelines

• Fully interactive notebook with collaboration, dashboards, REST APIs

• Advanced security, role-based access controls, and audit logs

• Single Sign On support

• Integration with BI tools such as Tableau, Qlik, and Looker