Lazy evaluation is one of the most powerful concepts in Apache Spark that significantly optimizes the execution of big data processing workflows. It allows Spark to defer computation until an action is performed, thereby improving efficiency and resource utilization. In this blog, we will explore lazy evaluation in Databricks PySpark with detailed explanations, examples, and
1.What is Azure Data Factory? Answer: Azure Data Factory is a cloud-based, fully managed, server less ETL and data integration service offered by Microsoft Azure for automating data movement from its native place to say a data lake or data warehouse using ETL (extract-transform-load) OR extract-load-transform (ELT). It lets you create and run data pipelines that
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Embark on a transformative journey into the realm of Azure Data Engineering with our comprehensive course. Dive deep into the core elements of SQL Server, Azure Data Factory, Databricks PySpark, Delta Lake, Data Warehouse concepts, Logic App for seamless notifications, and Key Vault for secure secrets storage. This course is not just about theory; it’s
