Is 'Azure Databricks' part of your next Analytics implementation? Here's a closer look at Microsoft Azure Data Bricks

In this current crisis of COVID-19 worldwide, organizations are depending on reliable and accurate data resources – they need it to make informed data-driven decisions. And, Big data and Machine Learning lies at the heart of efforts; for comprehending and forecasting the impact of Coronavirus on their business.

We know that when we say Big Data and Machine Learning integration with data sources – it doesn’t only include running trained ML models. But it needs big data preparation, ELT processes, data transformation and ML models to achieve the full potential of your data.

From the arsenal of data engineering tools, Databricks is the market-leading, cloud-based tool used to process, transform and explore enormous volume of data through ML models. It’s the latest addition as a big data tool for the Microsoft Azure cloud – Azure Databricks. This Azure cloud service offers a collaborative and fast Apache Spark™ based Analytics platform. Backed by industry leading SLAs, it simplifies the process of creating big data and AI solutions.

Here’s why business need to consider Azure Databricks while narrowing on an Analytics implementation.

• Accelerate Machine Learning on Big data

  Businesses can unlock advanced automated Machine Learning capabilities. Data scientists can quickly identify suitable hyperparameters and algorithms. It is enabling DevOps for ML to simplify monitoring, management, and updating of ML models. Azure Databricks also offer a central registry for ML experiments, pipelines, and models being created across the organization

• Faster Modern data warehousing capabilities

  As far as data warehousing go, Microsoft Azure enables high-performance and unmatched levels of scalability. You can automate data movement and load data using Azure Data Factory & Data Lake Storage, then transform & clean it quickly by leveraging Azure Databricks. Get business-critical insights through operational reports and analytical dashboards.

• Boost productivity with higher collaboration workspace & languages familiarity

  You don’t have to break your head on how to develop using Azure Databricks. It allows you to build using common languages, including Python, R, SQL and Scala. Version control is also made easy with Azure DevOps and GitHub.

• Easy integration with whole Microsoft Stack

  If you’ve been using Microsoft Azure, integrating Azure Databricks with existing business environment will seem effortless to you. Azure Databricks uses the Azure Active Directory (AAD) security framework that allows simple integration with Azure components like Data Warehouse, Blog Storage and Azure Event hub - acts as a premier alternative to Azure Data Lake Analytics and Azure HDInsight. Take help from top-notch Azure Analytics consulting firms to utilize Azure Databricks for your next analytics innovation – and go-to-market quickly.

• Suitable to smaller scale jobs too

  Azure Databricks is a one-stop-shop for all your analytical needs. No need to build separate VMs or environments for development work using Azure Databricks. Though it is ideal for massive complex jobs, you can use it for small jobs as well.