Boosting Data Ingestion in Data Factory: Continuous Innovations in Performance Optimization
At Fabric Data Factory, we’re committed to delivering continuous improvements to optimize data ingestion performance and streamline the user experience. Our latest technical innovations enhance performance across various aspects of Data Factory, from handling binary data more effectively to delivering faster data preview and navigation. Here’s a closer look at how these advancements are transforming data ingestion in Data Factory.
1. Efficiently Moving Binary Data from Source to Sink
Binary copy in data integration is a valuable approach, particularly when dealing with large datasets and diverse file formats that need to be moved efficiently across platforms. Unlike traditional data copy, which may involve transformations, binary copy transfers data as-is, directly in its native binary format.
Users today can already utilize the highly performant binary copy capability in Data Factory. On top of that, we are exploring to leverage techniques across the broad to optimize the binary copy throughput upper limit by 10-20% for a subset of copy pairs, including writing data among Azure Data Lake gen2, Azure Blob Storage, Fabric Lakehouse files, Amazon S3 and more. This enhancement will be automatically applied to the data movement jobs where applicable, requiring no additional configuration from users. As a result, data transfers will be completed faster and at a lower cost, further optimizing both time and resources in data integration workflows.
2. Improved Performance on Test Connection
Testing connections is a crucial step in building robust data pipelines, helping teams verify connectivity and troubleshoot potential issues before launching full data flows. Recognizing the need for speed in this step, we’ve introduced significant performance improvements to the Test Connector function. These optimizations enable quicker testing cycles, empowering users to validate their connections with minimal delay.
Key Benefits:
- Faster Pipeline Validation: Users can validate connectors in a fraction of the time, expediting pipeline setup and reducing overall development time.
- Streamlined Troubleshooting: With quicker test cycles, users can troubleshoot connectivity issues faster, minimizing downtime and maximizing productivity.
- Optimized Workflow: Faster testing supports an agile approach to building pipelines, making it easier to iterate and refine workflows without sacrificing quality.
3. Enhanced Data Navigation Experience
Smooth navigation within data pipelines is essential for managing complex workflows. To enhance the user experience, we have made further optimization to enhance data navigation performance that make it quicker for users to move through datasets and tables with speed and ease. This update includes more responsive browsing, allowing users to access their data quickly and confidently.
Key Benefits:
- Faster Dataset Browsing: With improved navigation, users can access and organize datasets more efficiently, reducing time spent waiting for information.
- Simplified Data Management: Enhanced navigation allows users to handle large datasets seamlessly, improving productivity in managing data pipelines.
4. Accelerated Data Preview for Quick Validation
Data preview is an invaluable functionality for validating data correctness and structure before launching full ingestion workflows. We understand the importance of fast, accurate previews, which is why we invest significant effort in improving the data preview function. With this update, users can preview their data more rapidly, ensuring that it meets the required standards before processing.
Key Benefits:
- Reduced Waiting Time: Enhanced preview speeds mean that users spend less time waiting, enabling faster data validation and fewer interruptions in workflow.
- Improved Data Quality Control: By allowing for rapid data previews, this update empowers teams to catch errors early, maintaining data quality and reducing rework.
- Enhanced User Experience: Faster data preview provides a smoother experience, especially when working with larger datasets, giving users a better overall view of their data before ingestion.
5. Optimize Schema Import for Accurate Data Structuring
Schema import is crucial for ensuring that data is correctly structured and organized before ingestion. Our latest improvements to schema import performance speed up the process, allowing users to quickly and accurately configure schemas from source systems. This enhancement reduces the time and complexity associated with defining and mapping data structures, making it easier to manage large or complex datasets.
Key Benefits:
- Faster Schema Configuration: Accelerated schema import reduces the time needed to set up data structures, enabling teams to integrate new data sources more quickly.
- Reduced Setup Complexity: Simplified schema import streamlines the setup process, making it easier for users to get pipelines up and running without extensive configuration.
In general, the overall improved duration for user to conduct above operations (mentioned in 2 – 5) has been reduced from 15 seconds to less than 3 seconds.
Pushing the Boundaries of Performance in Data Factory
These innovations reflect our ongoing commitment to delivering a powerful, streamlined data ingestion experience for our users. With each enhancement, we’re making it easier for organizations to handle complex data workflows, manage vast datasets, and optimize resource usage without sacrificing performance. By continuing to push the boundaries of what’s possible, Fabric Data Factory is empowering data teams to achieve faster, more efficient results.
Looking Forward: What’s Next for Data Factory?
Our work doesn’t stop here. We’re constantly exploring new ways to enhance performance, optimize resource usage, and provide users with the tools they need to manage data ingestion effectively. In the coming months, expect to see further improvements aimed at scalability, additional connectors, and advanced performance tuning options to support even the most demanding data workflows.
Get Started with These New Features
All these performance enhancements are now available in Fabric Data Factory, ready to be explored. We’re excited to see how these new capabilities will accelerate your data workflows and empower your organization’s data journey.
