Azure Databricks: What is it and three benefits to choose it.

Data-driven decision making is the key behind all strategic decisions of companies. Large volumes of data flow from different sources of origin to the data warehouse or any analysis tool to obtain information. Companies require having a fast, reliable, scalable and easy-to-use workspace for data engineers, data analysts and data scientists.

Today, as the amount and complexity of information increases, the problem of processing and leveraging data becomes more complex to unify. The ability of teams to prototype and operationalize data-based solutions is also hindered by fragmented systems and instruments, each with restricted capabilities, as well as the inability to use data science to create smarter options.

Information experts face difficulties in closing the gap between raw data and value-creating alternatives, some of these difficulties are:

• Providing simple and fast access to information at scale.

• Implementing machine learning and streaming applications of production quality.

• Using more data science to support decision making.

Providing simple and fast access to information at scale.

It means processing structured and unstructured data, ingesting from non-traditional data storages reducing batch processing time.

Implementing machine learning and streaming applications of production quality.

Configuring, tuning and scaling Apache Spark clusters for the team. Keeping the clusters resilient and updated with the latest versions. Scheduling, running and debugging applications in production.

Using more data science to support decision making.

Which points to interactive data exploration and visualization, creating real-time dashboards and connecting to Business Intelligence tools.

Taking into account this and some additional problems in the unification of information that data science faces, this is where Databricks comes into play as a solution. Databricks is a cloud-based data engineering tool that businesses widely use to process and transform large amounts of data and explore them. It enables organizations to quickly achieve the full potential of combining their data, ETL (extract, transform and load) processes and Machine Learning.

Traditional Big Data processes are not only slow to perform tasks, but also consume more time to set up. However, Databricks is based on distributed cloud computing environments such as Azure, which makes it easy to run applications on CPU or GPU according to the analysis requirements. The Databricks platform is said to be 100 times faster than Apache Spark . It improves innovation, development and also provides better security.

Databricks is integrated with Microsoft Azure, which makes it a unified analytics platform (UAP), which accelerates innovation by unifying data science, engineering and business.

Here are some of the key reasons why Azure Databricks is a great choice for data science and big data workloads.

Azure Databricks: What is it and three benefits to choose it.

Reason #1: Speed

Anyone who is familiar with Apache Spark knows that it is fast. It can run up to 100 times faster than Hadoop MapReduce when running in memory, or up to 10 times faster when running on disk. Azure Databricks is even faster!

The Databricks team provides a number of performance enhancements on top of normal Apache Spark. These include caching, indexing, and advanced query optimizations. The benchmarking data below, from a recent post by Juliusz Sompolski and Reynold Xin on the Databricks Engineering Blog, show that these optimizations contribute to a performance increase of up to 8 times compared to other similar big data SQL platforms. Add that to the already 10 to 100x performance gains, and one can see the obvious processing efficiencies that this engine provides.

Reason #2: Security

Azure Databricks directly integrates with Azure Active Directory (AAD) immediately, without any custom configuration needed. This differs significantly from Apache Spark in Azure HDInsight, where AAD integration is a premium feature that requires considerable setup with Apache Ranger.

After creating the Azure Databricks service and initializing the Databricks workspace, users with access can simply go to the workspace URL and log in using their AAD credentials.

Once inside the Databricks workspace, administrative users can navigate to the management console, enabling them to easily add, remove, and manage users within the workspace. They can even invite external users (those who do not belong to the same AAD) to the workspace, provided the user belongs to another AAD.

Reason #3: Collaboration

Collaboration is the third reason for choosing Azure Databricks for data science and engineering workloads. Azure Databricks provides a platform where data scientists and data engineers can easily share workspaces, clusters, and jobs through a single interface. They can also push their code and artifacts to popular source control tools like GitHub.

Within Azure Databricks, users can start clusters, create interactive notebooks, and schedule jobs to execute notes. Using the Azure Databricks portal, users can easily share these artifacts with others. This enables users to collaboratively create and build models together in the same notebook in real-time, reuse data assets, libraries, and computing resources on the same cluster, or reuse and monitor scheduled jobs.

Data engineers and data scientists using popular source control tools like GitHub and Bitbucket to manage their code can continue doing so with Azure Databricks. This allows companies that have adopted independent source control processes across the enterprise to continue using their established methods. Azure Databricks facilitates linking and syncing artifacts such as Notes to a Git repository where they can exist, even if the Azure Databricks workspace disappears.

Azure Databricks, the new and exciting Azure service, helps companies innovate more effectively and efficiently alongside Big Data. If you're interested in learning more about this service and how it could fit into your company's data platform, please contact us or explore the data benefits in 2022 that we can provide.

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