Databricks has a free version (called Community Edition) and a paid version. What are the main differences between them, and what things can’t I do in the free version that I can do in the paid one?
When you create notebooks or jobs in Databricks, how does Databricks keep track of different versions or changes? And what should beginners do to manage versions safely and effectively?
You have some raw data (like messy Excel files, CSVs, or logs) and you want to prepare it for analysis — by removing errors, fixing missing values, changing formats, or combining columns — using PySpark (Python for Apache Spark) inside Databricks.
If your company uses Databricks with many people, how do you manage security, organize teams, and control costs — and what tools do you use to make it all work smoothly?
Leveraging Databricks Marketplace and API integrations can significantly streamline app development. By using pre-built datasets, notebooks, and APIs, developers can accelerate data workflows, reduce redundant coding, and ensure seamless integration ...
Developing and debugging Spark jobs in Databricks can be challenging due to the distributed nature of Spark and the volume of data processed. To streamline your workflow:Leverage Notebooks for Iterative Development:Use Databricks notebooks to write a...
