Databricks Certified Data Engineer - Professional
Get started today
Ultimate access to all questions.
Ultimate access to all questions.
Explain the process of incremental processing in a data pipeline. How does it differ from batch processing, and what are the key considerations for implementing incremental processing effectively?
Explanation:
Incremental processing is a method where only new or changed data since the last run is processed, which can be more efficient than batch processing that processes all data regardless of changes. Key considerations for implementing incremental processing effectively include identifying changes in data, managing dependencies, and ensuring data consistency across runs.