What is Databricks Data Science & Engineering?

Databricks Data Science & Engineering (sometimes called simply "Workspace") is an analytics platform based on Apache Spark. It is integrated with Azure to provide one-click setup, streamlined workflows, and an interactive workspace that enables collaboration between data engineers, data scientists, and machine learning engineers.

For a big data pipeline, the data (raw or structured) is ingested into Azure through Azure Data Factory in batches, or streamed near real-time using Apache Kafka, Event Hub, or IoT Hub. This data lands in a data lake for long term persisted storage, in Azure Blob Storage or Azure Data Lake Storage. As part of your analytics workflow, use Azure Databricks to read data from multiple data sources such as Azure Blob Storage, Azure Data Lake Storage, Azure Cosmos DB, or Azure SQL Data Warehouse and turn it into breakthrough insights using Spark.

Apache Spark analytics platform

Databricks Data Science & Engineering comprises the complete open-source Apache Spark cluster technologies and capabilities. Spark in Databricks Data Science & Engineering includes the following components:

◉ Spark SQL and DataFrames: Spark SQL is the Spark module for working with structured data. A DataFrame is a distributed collection of data organized into named columns. It is conceptually equivalent to a table in a relational database or a data frame in R/Python.

◉ Streaming: Real-time data processing and analysis for analytical and interactive applications. Integrates with HDFS, Flume, and Kafka.

◉ MLlib: Machine Learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as underlying optimization primitives.

◉ GraphX: Graphs and graph computation for a broad scope of use cases from cognitive analytics to data exploration.

◉ Spark Core API: Includes support for R, SQL, Python, Scala, and Java.

Apache Spark in Azure Databricks

Azure Databricks builds on the capabilities of Spark by providing a zero-management cloud platform that includes:

◉ Fully managed Spark clusters

◉ An interactive workspace for exploration and visualization

◉ A platform for powering your favorite Spark applications

Fully managed Apache Spark clusters in the cloud

Azure Databricks has a secure and reliable production environment in the cloud, managed and supported by Spark experts. You can:

◉ Create clusters in seconds.

◉ Dynamically autoscale clusters up and down and share them across teams.

◉ Use clusters programmatically by invoking REST APIs.

◉ Use secure data integration capabilities built on top of Spark that enable you to unify your data without centralization.

◉ Get instant access to the latest Apache Spark features with each release.

Databricks Runtime

Databricks Runtime is built on top of Apache Spark and is natively built for the Azure cloud.

Azure Databricks completely abstracts out the infrastructure complexity and the need for specialized expertise to set up and configure your data infrastructure.

For data engineers, who care about the performance of production jobs, Azure Databricks provides a Spark engine that is faster and performant through various optimizations at the I/O layer and processing layer (Databricks I/O).

Workspace for collaboration

Through a collaborative and integrated environment, Databricks Data Science & Engineering streamlines the process of exploring data, prototyping, and running data-driven applications in Spark.

◉ Determine how to use data with easy data exploration.

◉ Document your progress in notebooks in R, Python, Scala, or SQL.

◉ Visualize data in a few clicks, and use familiar tools like Matplotlib, ggplot, or d3.

◉ Use interactive dashboards to create dynamic reports.

◉ Use Spark and interact with the data simultaneously.

Enterprise security

Azure Databricks provides enterprise-grade Azure security, including Azure Active Directory integration, role-based controls, and SLAs that protect your data and your business.

◉ Integration with Azure Active Directory enables you to run complete Azure-based solutions using Azure Databricks.

◉ Azure Databricks roles-based access enables fine-grained user permissions for notebooks, clusters, jobs, and data.

◉ Enterprise-grade SLAs.

Integration with Azure services

Databricks Data Science & Engineering integrates deeply with Azure databases and stores: Synapse Analytics, Cosmos DB, Data Lake Store, and Blob storage.

Integration with Power BI

Through rich integration with Power BI, Databricks Data Science & Engineering allows you to discover and share your impactful insights quickly and easily. You can use other BI tools as well, such as Tableau Software.

Source: microsoft.com