Data processing in the cloud has become increasingly popular due to its scalability, flexibility, and cost-effectiveness. Modern tech stacks such as Apache Spark, Azure Data Factory, Azure Databricks, and Azure Synapse Analytics offer powerful tools for building optimized data pipelines that can efficiently ingest and process data on the cloud. This article will explore how these technologies can be used together to create an optimized data pipeline for data processing in the cloud.
Ingesting Data With Azure Data Factory
Azure Data Factory is a cloud-based data integration service enabling you to ingest data from various sources into a cloud-based data lake or warehouse. It provides built-in connectors for various data sources such as databases, file systems, cloud storage, and more. In addition, you can configure Data Factory to schedule and orchestrate data ingestion processes and define data flow transformations.