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Understanding The Azure Databricks Purpose
The Big Data industry experts are predicting that within the next five years, the Big Data reserves around the world would get increased from 4.4 zettabytes to around 44zettabytes. To handle this massive volume of Big Data & to accurately extract the insights from it, enterprises need to work on the right data tools.
As per the experts opinion, only 10% of the overall Big Data which is available around the world is in structured format & the rest 90% of the data is in unstructured format. To efficiently handle this unstructured data of sheer volume, using advanced analytics tools like Apache Spark is highly essential. Apache Spark is capable of handling massive clusters of databases and servers to accurately explore the data.
This is where Azure Databricks jumps in. It can be interpreted as a cloud-optimized version of Apache Spark. The Microsoft Foundation has researched extensively to integrate Apache Databricks with Microsoft Azure & has been highly successful in achieving this goal. Experts have coined Azure Databricks as the perfect analytics solution which is available for businesses on the Azure Cloud platform. Build real-time expertise in handling Azure Databricks by joining for the Best Azure Databricks Training In Hyderabad program by OST.
Databricks can be interpreted as an advanced data engineering tool which is capable of delivering business solutions by accurately analyzing the data though Machine Learning models.
Now, let’s have a look at the Databricks purposes.
Makes Use of Commonly Used Programming Languages & Environment-
With Databricks, users can work on the most popular & extensively used languages like Python, R, and SQL. This system makes use of APIs to convert these languages in the background to interact with Spark. With this set of approach, users can be benefited a lot as they no longer require to learn specific programming languages for specific analytics operations.
Can Be Easily Integrated With Microsoft Stack-
Azure Databricks makes extensive use of Azure Active Directory (AAD) security framework. Users can make use of existing credentials authorization with the corresponding security settings. Users no longer need to have multiple environments for managing access and identity control. With Azure Active Directory, it becomes possible to integrate the Azure stack completely along with Data Lake Storage.
Extensive List Of Data Sources-
In addition to connecting with Azure-based sources, Databricks can also get connected to SQL servers, CSVs, and JSONs, etc
Has Extensive Documentation & Support-
Databricks is in existence from a long time even before its addition to Azure. So working in this platform wouldn’t be much difficult as it has the presence of extensive documentation and support in every aspect.
Azure Databricks is the best cost effective solution for handling enterprises distributed analytics operations.