Building Enterprise-Grade Data Pipelines Using Synapse Pipelines in Azure Synapse Analytics by Abhishek Narain (Recordings)
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Building Enterprise-Grade Data Pipelines Using Synapse Pipelines in Azure Synapse Analytics
8-hrs Video Course (Recorded Class)
Subscription Period: Lifetime Access
Abstract: Azure Synapse is an integrated analytics service that accelerates time to insight across data warehouses and big data analytics systems. At its core, Azure Synapse brings together the best of SQL technologies used in enterprise data warehousing, Spark technologies used for big data, and Pipelines for data integration and ETL/ELT. Synapse has a web-based Studio that provides a single place for management, monitoring, coding, and security.
In this training, we will deep-dive into Synapse Pipelines, which focusses on data engineers targeting to integrate and transform big data workloads, batch-based, on Azure using Synapse Analytics.
Modules:
- Synapse pipelines overview
- Extract data using 90+ data connectors
- Transform and Load data using code-free data flows
- ETL patterns and practices – metadata-driven workflows, event-driven data processing pipelines, CI/CD, security, pipeline monitoring and alerting
Description
Building Enterprise-Grade Data Pipelines Using Synapse Pipelines in Azure Synapse Analytics
Abstract: Azure Synapse is an integrated analytics service that accelerates time to insight across data warehouses and big data analytics systems. At its core, Azure Synapse brings together the best of SQL technologies used in enterprise data warehousing, Spark technologies used for big data, and Pipelines for data integration and ETL/ELT. Synapse has a web-based Studio that provides a single place for management, monitoring, coding, and security.
In this training, we will deep-dive into Synapse Pipelines, which focusses on data engineers targeting to integrate and transform big data workloads, batch-based, on Azure using Synapse Analytics.
Modules:
- Synapse pipelines overview
- Extract data using 90+ data connectors
- Transform and Load data using code-free data flows
- ETL patterns and practices – metadata-driven workflows, event-driven data processing pipelines, CI/CD, security, pipeline monitoring and alerting