Importing Sample Data for Practice

You have your Workspace set up, and your Cluster is running. Now, we need something to work with. In the real world, data might come from streaming sensors or massive cloud databases, but most data projects start with a simple file. In this chapter, we will use the modern Data Ingestion capability to upload a CSV file and turn it into a permanent table in your Catalog.

Accessing Data Ingestion

There are two quick ways to find this tool:

• Click the "New" button at the top of the sidebar and select "File Upload".
• Alternatively, go to the Catalog tab and click the "Create Table" button (often represented by a plus sign).

Step 2: Uploading the File

Once you are in the upload interface, you can drag and drop your file or browse your computer.

• The Scenario: for this exercise, we are using a sample file called diamonds.csv;
• The Upload: once the file is uploaded, Databricks will store it temporarily in a "staging" area while it prepares to move it into the Catalog.

Step 3: Configuring the Table (The Preview)

This is where the "magic" happens. Databricks will show you a preview of your data.

• Catalog and Schema: you must choose where the table will live. For now, we will use the workspace catalog and the default schema;
• Table Name: give your table a clear name, such as diamonds;
• Data Types: Look at the columns. Databricks automatically guesses if a column is a "String" (text), an "Integer" (number), or a "Timestamp" (date). If it guesses wrong, you can manually change the data type right here in the UI.

Step 4: Creating the Table

Click Create Table. Databricks will now start a small background job (using your cluster) to read the CSV and write it as a high-performance Delta Table. Once finished, you will be taken to the Table UI, where you can see the schema, sample data, and even who has permission to view it.

Congratulations! You have successfully moved data from your personal computer into the cloud-native Lakehouse.