An Azure analytics service that brings together data integration, enterprise data warehousing, and big data analytics. Previously known as Azure SQL Data Warehouse.
@Niren Adhikary - Thanks for the question and using MS Q&A platform.
If you have views and pipelines already created in Azure Synapse Analytics and you need to refresh the data, there are several options you can consider:
- Use a pipeline to refresh the data: You can create a pipeline in Azure Synapse Analytics that refreshes the data in your views. You can use activities such as Copy Data or Data Flow to extract data from your source systems and load it into your views. You can then schedule the pipeline to run on a regular basis to keep your views up-to-date.
- Use a trigger to refresh the data: You can create a trigger in Azure Synapse Analytics that automatically refreshes the data in your views based on a schedule or event. You can use the trigger to start a pipeline that extracts data from your source systems and loads it into your views.
- Use Azure Data Factory or Azure Databricks: If you need more advanced data transformation capabilities, you can use Azure Data Factory or Azure Databricks to extract data from your source systems, transform it, and load it into your views. You can then schedule the pipeline or job to run on a regular basis to keep your views up-to-date.
- Use Azure Stream Analytics: If you need to refresh your views in real-time, you can use Azure Stream Analytics to process streaming data and update your views in real-time.
It's important to note that when you refresh the data in your views, you may need to update your downstream pipelines and reports to reflect the changes in the data. You should also consider the impact of data refresh on your system performance and resource utilization.
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