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Enabling modern data integration in Azure cloud

Submitted by Abhishek Narain (@narainabhishek) on Friday, 2 November 2018

Technical level: Intermediate

Abstract

This session walks through a comprehensive set of new additions to Azure Data Factory (ADF) and SQL Server Integration Services (SSIS) for moving and integrating data across on-premises and cloud. Topics and examples focus on the needs of the data integrator and data engineer for data warehousing with Big Data, business intelligence, and advanced analytics in SaaS applications. Learn how Microsoft has enabled simple, scalable, and reliable data pipelines in ADF using a serverless, hybrid, parallel data movement service to lift and shift SSIS packages and create new modern ETL/ELT workflows in a code-free environment for your Big Data workload.

Outline

  1. ETL/ ELT options on Azure
  2. Why Azure Data Factory (ADF)?
  3. End-to-end demos- ETL with SSIS on Cloud (lift-and-shift) using ADF, ETL with databricks using ADF
  4. Customer use-cases and learnings

Speaker bio

Abhishek works as a Program Manager in Azure Data group, focusing on Information Management stack (Azure Data Factory). He has earlier worked as a Consultant and Technical Evangelist at Microsoft working on Azure – IoT, Big Data, PaaS services and helped Partners/ ISVs architect scalable applications on Azure.

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