SQLBits 2022
The Dream Team: Synapse Analytics Serverless SQL Pools and Pipelines
Synapse Analytics Serverless SQL Pools and Pipelines are the dream team when it comes to managing big data in Azure Data Lake, this session will take you through the process!
Synapse Analytics is Microsoft's flagship limitless data analytics service. In this session we'll look at how Serverless SQL Pools and Pipelines are the ultimate dream team, working together to ingest, transform, and serve data stored in Azure Data Lake Gen2.
Within Synapse Analytics, Serverless SQL Pools allows the reading and writing of data stored externally in Azure Storage, Data Lake, Cosmos DB, and the Dataverse. Pipelines allow the transformation of data between data services at scale including Azure Storage and Data Lake.
1. Discuss the architecture of Synapse Analytics with Serverless SQL Pools, Pipelines, and Data Lake Gen2
2. Use Synapse Analytics Pipelines to transform raw CSV data into enriched Parquet data in the Data Lake
3. Connect Synapse Analytics Serverless SQL Pools to the enriched Parquet data for analysis
After this session you'll have an understanding of the benefits that Synapse Analytics Serverless SQL Pools and Pipelines have when working with data stored in Azure Data Lake Gen2
Feedback Link - https://sqlb.it/?6996
Within Synapse Analytics, Serverless SQL Pools allows the reading and writing of data stored externally in Azure Storage, Data Lake, Cosmos DB, and the Dataverse. Pipelines allow the transformation of data between data services at scale including Azure Storage and Data Lake.
1. Discuss the architecture of Synapse Analytics with Serverless SQL Pools, Pipelines, and Data Lake Gen2
2. Use Synapse Analytics Pipelines to transform raw CSV data into enriched Parquet data in the Data Lake
3. Connect Synapse Analytics Serverless SQL Pools to the enriched Parquet data for analysis
After this session you'll have an understanding of the benefits that Synapse Analytics Serverless SQL Pools and Pipelines have when working with data stored in Azure Data Lake Gen2
Feedback Link - https://sqlb.it/?6996