Azure Databricks Notebook


       Azure Databricks Notebook

Azure Databricks Notebooks are interactive environments where you can develop code, visualize data, and collaborate with others. They are a primary tool for data scientists, machine learning engineers, and analysts on the Azure Databricks platform.

Key features and capabilities of Azure Databricks Notebooks:

  • Language Support: Flexibility is at your fingertips as you can develop code using Python, SQL, Scala, and R in the same notebook, allowing you to adapt and be versatile.Real-Time Collaboration: Multiple users can edit and run code simultaneously on the same laptop, fostering collaboration.
  • Automatic Versioning: Rest easy knowing that your notebooks are automatically versioned. This makes it a breeze to track changes and revert to previous versions, instilling a sense of confidence in your work. Data Visualizations: Create rich visualizations within the notebook to explore and understand your data.
  • Integration with the Lakehouse: Seamlessly work with data stored in the Databricks Lakehouse, a unified platform for data warehousing and AI.
  • Scheduled Jobs: You can schedule notebooks to run automatically at specific times or intervals, allowing you to automate data pipelines and reporting.

Getting started with Azure Databricks Notebooks:

  1. Create a notebook:
    • Click “New” in the sidebar and select “Notebook.”
    • Give your notebook a name and choose the default language.
    • Select a compute resource or create a new one.
  2. Write code:
    • Notebooks are divided into cells. Each cell can contain code, text, or visualizations.
    • Use the appropriate language magic command to specify the language for each cell (e.g., %python, %sql, % scale, %r).
    • Run cells individually or in sequence.
  3. Explore data:
    • Use SQL to query data from your Lakehouse or external data sources.
    • Utilize Python, R, or Scala libraries for data manipulation and analysis.
    • Create visualizations using Matplotlib, Seaborn, ggplot2, or other libraries.
  4. Collaborate:
    • Share notebooks with others in your workspace.
    • Use comments to communicate with collaborators.
    • Track changes and version history.

Databricks Training Demo Day 1 Video:

You can find more information about Databricks Training in this Dtabricks Docs Link



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