How to Use Databricks

Getting started with Databricks

In this guide, you'll learn how to set up your Databricks account and perform your first data analysis task. By the end, you'll be able to navigate the platform and start working with your data efficiently.

Step 1: Sign up and set up

1. Go to Databricks.
2. Click on the "Get Started for Free" button on the homepage.
3. Fill in the required information, including your name, email, and company details.
4. Confirm your email address through the verification link sent to your inbox.
5. Once verified, log in to your new Databricks account.

Step 2: Your first notebook

1. After logging in, click on the "Workspace" tab in the left sidebar.
2. Click on the “Create” button and select “Notebook”.
3. Name your notebook (e.g., "My First Analysis") and choose a default language (Python is recommended).
4. Use the cell provided to enter your first command. For example, type:

print("Hello, Databricks!")

1. Click the "Run" button (the play icon) to execute your command. You should see the output below.

Step 3: Get better results

1. To import data, click on the “Data” tab in the left sidebar.
2. Click on “Add Data” and choose a data source (e.g., upload a CSV file or connect to an existing database).
3. Once your data is loaded, use SQL or Python commands to query and analyse it. For example, use:

df = spark.read.csv("/path/to/your/file.csv", header=True)  
   df.show()

1. Explore visualisation options by clicking the "Visualisations" tab after running a query to create charts or graphs for better insights.

Pro tip

Use the command palette by pressing Cmd + Shift + P (Mac) or Ctrl + Shift + P (Windows) to quickly access functions, create new notebooks, and navigate your workspace without using the mouse.

Common mistake to avoid

A frequent error is not setting the correct cluster when running your code. Make sure you have a cluster running before executing any commands. You can check this by clicking on the “Clusters” tab in the left sidebar and starting a cluster if necessary.