The Benefits of Using Databricks

Why Use Databricks

 

 

 

What is Datrabricks?

 

Databricks is an industry-leading, cloud-based data engineering tool used for processing and transforming massive quantities of data and exploring the data through machine learning models.

 

Databricks is integrated with Microsoft Azure, Amazon Web Services, and Google Cloud Platform to make it easier for businesses to manage a substantial amount of data and carry out machine learning tasks.

 

Here are some benefits of learning Databricks :

 

High Productivity

Databricks provides an inter-professional environment with a common workspace for data scientists, engineers, and business analysts. Collaboration not only brings new and fresh ideas, but it also allows others to introduce frequent changes while boosting development processes concurrently. Deploying work from Notebooks into production can be done almost instantly by just tweaking the data sources and output directories.

 

Flexible

Since Databricks is developed by the creators of Apache Spark, it is optimized for cloud environments. Databricks provides scalable Spark jobs in the data science domain. It is flexible for small-scale jobs like development or testing as well as running large-scale jobs like Big Data processing. For those who are just starting their programming journey, you can easily switch between the different languages on Databricks. This is convenient when functions from different languages are needed.

 

Data Source

Databricks connects with many data sources to perform limitless Big Data Analytics. Databricks not only connects with cloud storage services provided by AWS, Azure, or Google Cloud but also connects to on-premise SQL servers, CSV, and JSON.

 

Can be used for small jobs

Databricks is ideal for massive jobs, but it can be used for smaller scale jobs, and development or testing work as well. Databricks can be used as a one-stop shop for all analytics work.

Databricks was created for data scientists, analysts, and engineers to help users integrate the fields of data science and engineering across the machine learning lifecycle. It helps ease the processes from data preparation to experimentation and machine learning application deployment.

 

Contact P2L today to learn more about Databricks.

 

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