Azure Data Factory was launched by Microsoft in 2014 as part of its Azure cloud services. It was created to address the need for a scalable and flexible data integration service that could manage complex data workflows and facilitate seamless data movement and transformation in cloud-based environments.
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that allows users to create, schedule, and orchestrate data workflows. It enables the movement and transformation of data across various services and environments, facilitating the creation of data-driven workflows for orchestrating and automating data movement and transformation.
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About Azure Data Factory
Azure Data Factory's strengths include its scalability, integration with diverse data sources, and robust orchestration capabilities. Weaknesses may involve a steep learning curve for new users and potential cost complexities. Competitors include AWS Glue, Google Cloud Dataflow, and Talend.
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How to hire a Azure Data Factory expert
An Azure Data Factory expert must have skills in data integration and ETL processes, proficiency in using Azure services like Azure Storage and Azure SQL Database, experience with data transformation using Data Flow, and knowledge of programming languages such as SQL and Python. Familiarity with Azure DevOps for CI/CD pipelines and understanding of JSON for pipeline configuration are also important.
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