Change Data Capture and Managed Airflow in Azure Data Factory | Azure Friday
"Change Data Capture and Managed Airflow in Azure Data Factory | Azure Friday" is a video focused on showcasing how Change Data Capture (CDC) and Managed Airflow can be used in Azure Data Factory to efficiently track changes in data and automate workflows. Azure Data Factory is a cloud-based platform for data integration that allows data engineers to ingest, transform, and load data from multiple sources seamlessly.
In this video, the hosts explore how CDC can be used to efficiently capture and track changes in data by identifying inserted, updated, and deleted records in real-time. This enables data engineers to respond faster to changes, as well as automate workflows to update downstream systems that need to be informed of data changes.
Additionally, the hosts dive into Managed Airflow, a new feature in Azure Data Factory that enables customers to autogenerate workflows in Airflow. With Managed Airflow, data engineers can also orchestrate workflows in a serverless environment, reducing overhead costs and complexity. Additionally, the platform provides flexible scaling capabilities and built-in monitoring tools that enable data engineers to effectively manage and orchestrate workflows.
In summary, if you're a data engineer looking to streamline workflows, foster collaboration between teams, and increase efficiency in data integration, this video provides valuable insights into how Change Data Capture and Managed Airflow can serve as powerful tools in meeting these needs.
The link to the video is: https://www.youtube.com/watch?v=GaWlhlReoA8.
Published on:
Learn moreRelated posts
Mastering Microsoft Purview Workflow: Revolutionize Your Data Governance
If you're struggling to manage your ever-growing data landscapes while ensuring compliance, quality, and collaboration, then Microsoft Purview...
Incrementally loading files from SharePoint to Azure Data Lake using Data Factory
If you're looking to enhance your data platform with useful information stored in files like Excel, MS Access, and CSV that are usually kept i...
Azure Data Transfer authorized for Azure Government Secret and generally available for critical mission data types
Azure Data Transfer has secured an important provisional authorization from the Department of Defense (DoD) Impact Level 6 (IL6). This enables...
Using variables in loops in Data Factory – why it’s not worth it
In this post, the author discourages the use of variables in loops in Data Factory. Loo...
Refreshing a Power BI Dataset using Azure Data Factory
If you're looking for a more efficient way to refresh your Power BI dataset, this article has got you covered. While the built-in schedule in ...
Streamline Your Big Data Projects Using Databricks Workflows
Databricks Workflows can be an incredibly handy tool for data engineers and scientists alike, streamlining the process of executing complex pi...
Dealing with ParquetInvalidColumnName error in Azure Data Factory
Azure Data Factory and Integrated Pipelines within the Synapse Analytics suite are powerful tools for orchestrating data extraction. It is a c...
Azure Data Factory (ADF) Quick Tip: Incremental Data Refresh in Cosmos DB – Change Feed Capture
This video delves into a quick and actionable tip for Azure Data Factory (ADF) users seeking to implement incremental data refresh in Cosmos D...
Azure Data Factory (ADF) Quick Tip: Implement Easy Data Validations Using Assert Transform
Learn how to quickly and easily implement data validations in Azure Data Factory (ADF) with the Assert Transform feature. This brief but infor...