Here’s a breakdown of how to access Databricks, including the different scenarios and methods:

Prerequisites

• AWS or Azure Account:  Databricks are usually deployed within cloud environments. You’ll need an active AWS or Azure account to get started.

Methods to Access Databricks

There are a few ways to get up and running:

1. Create a New Databricks Workspace

1. 1. On AWS: Go to the AWS Marketplace and search “Databricks.”
   2. Start a free trial or select a paid pricing tier.
   3. Follow the guided setup to create your Databricks workspace within AWS.
   4. On Azure: In the Azure Portal, select “Create a resource” and choose “Azure Databricks.”
   5. Specify details like region, pricing tier, and resource group.
   6. Follow the setup to create your workspace.

2. Access an Existing Databricks Workspace

• • If your organization has an existing workspace, you’ll need these details from your administrator: Workspace URL: Usually in the format https://<region>.azuredatabricks.net or https://<aws-region>.cloud.databricks.com
  • Login Credentials: Depending on setup, this could be your username and password or integrated with your organization’s single sign-on (SSO) system.

3. Accessing Databricks from Your Development Environment

To work with Databricks programmatically, you’ll need tools and libraries:

• • Databricks CLI: Install the Databricks CLI using pip install data bricks-cli
  • Configure the CLI with your workspace URL and an access token (found in your Databricks User Settings).
  • Databricks Connect: This lets you connect to Databricks from development environments like PyCharm, IntelliJ, or VS Code. Install and configure it according to your chosen IDE: https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/

Steps: Once You Have Access

1. Log in: Go to your workspace URL and use the credentials you provided.
2. Explore the Interface: Get familiar with the notebooks, clusters, data management, and other features.
3. Start Learning: Databricks offers excellent documentation and tutorials: https://docs.databricks.com/en/getting-started/index.html.