Azure Data Factory: An orchestration service that allows users to create, schedule, and manage data pipelines, enabling the movement and transformation of data across on-premises and cloud environments.
Azure Data bricks: A collaborative Apache Spark-based analytics platform that facilitates big data processing, data exploration, and machine learning, providing an interactive and scalable environment.
Azure Stream Analytics: A real-time analytics service for processing and analyzing streaming data in real-time, enabling quick insights and actions based on the continuous flow of data.
Azure
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Efficiency: Incremental loading reduces the amount of data transferred between systems, making the data integration process more efficient. This is particularly important when dealing with large datasets.
Faster Updates: Since only the changed or new records are processed, incremental loading typically results in faster update times compared to reloading the entire dataset.
Reduced Resource Usage: Incremental loading minimizes the impact on system resources, such as network bandwidth, storage, and processing power.
Incremental loading is widely used in data warehousing, business intelligen
Faster Updates: Since only the changed or new records are processed, incremental loading typically results in faster update times compared to reloading the entire dataset.
Reduced Resource Usage: Incremental loading minimizes the impact on system resources, such as network bandwidth, storage, and processing power.
Incremental loading is widely used in data warehousing, business intelligen