Databricks Data Analyst Practice Exam

Data ingestion in Databricks can be accomplished through various methods, which allows for a flexible approach to loading data into the workspace. The correct choice highlights that data can be ingested using API calls, data connectors, and file uploads.

API calls allow users to programmatically access and load data from external systems, which is especially useful for integrating dynamic data streams. Data connectors facilitate easy access to a variety of data sources like databases, data lakes, and cloud storage, simplifying the process of connecting to source data without requiring manual uploads. Additionally, file uploads enable users to bring in static files directly from their local machines or cloud storage into the Databricks environment.

This comprehensive approach to data ingestion supports a wide range of data types and use cases, making it adaptable to the varying demands of analysis and processing. Therefore, the inclusion of multiple methods for data ingestion ensures that users can efficiently leverage Databricks for their data analytics needs.

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