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Azure Data Factory v2


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Big data requires service that can orchestrate and operationalize processes to refine the enormous stores of raw data into actionable business insights. Azure Data Factory is a managed cloud service that's built for these complex hybrid extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects.

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Azure Data Factory v2

  1. 1. Unleash the power of Azure Data Factory Sergio Zenatti Filho, Associate Director Data & Analytics, Satalyst
  2. 2. Sergio Zenatti Filho Associate Director Data &Analytics at Satalyst I am Data and Analytics Director with over 16 years experience in the delivery of Business Intelligence and Analytics Solutions. I worked internationally around Australia, New Zealand and Brazil, in sectors that include Mining, Oil & Gas, Government, Healthcare, Financial Services, Telecom, Automotive and dairy. I enjoy learning new technology and help people to learn. • MCSE: Data Management and Analytics • MCSE: Business Intelligence • MCSA: Cloud Platform • Perth SQL Server User Group Leader P lace your photo here /sergiozenatti @SergioZenatti
  3. 3. Session objectives
  4. 4. Azure Data Factory • Cloud-based data integration service. • Used to automate the movement and transformation of data. • Connect to on-premises and cloud data sources. • Integration with HDInsight, Azure Batch, Azure Functions, Logic Apps and more. • Globally deployed data movement as a service (Integration Runtime).
  5. 5. ADF v1, v2 and new Features • ADF v1 (GA) is designed for the batch data processing of time series data. • ADF v2 (Preview) is general-purpose hybrid data integration service with very flexible execution patterns. ADF v2 – New Features
  6. 6. ADF Components Source: A CSV File with ICT Jobs in Australia (from, around 11k records. Sink (Destination): Position Table
  7. 7. ADF Activities Options • Data Movement • Data Transformation • Control
  8. 8. How Azure Data Factory Works Data Integration capability • Data movement: Move data between data stores in public network and data stores in private network. • Activity dispatch: Dispatch and monitor transformation activities running on a variety of compute services such as Azure HDInsight, Azure Machine Learning, Azure SQL Database, SQL Server, and more. • SSIS package execution: Natively execute SSIS packages in a managed Azure compute environment.
  9. 9. ADF – Data Integration Scenario • Process around 15k XML files a day with total size around 6-7 GB • Infrastructure cost: max $5k a month • Process files once every hour • ADF, Logic Apps, Azure Data Lake, Azure SQL DW and Azure Analysis Services
  10. 10. ADF – Real Life Scenario • Azure SQL Data Warehouse – Expensive to run (Option to pause and resume) POST{subscription-id}/resourceGroups/{resource-group- name}/providers/Microsoft.Sql/servers/{server-name}/databases/{database-name}/pause?api-version=2014-04-01-preview HTTP/1.1 GET{subscription-id}/resourceGroups/{resource-group- name}/providers/Microsoft.Sql/servers/{server-name}/databases/{database-name}?api-version=2014-04-01 HTTP/1.1 POST{subscription-id}/resourceGroups/{resource-group- name}/providers/Microsoft.Sql/servers/{server-name}/databases/{database-name}/resume?api-version=2014-04-01-preview HTTP/1.1
  11. 11. ADF – Real Life Scenario • Azure Analysis Services – Process data model after data load POST https://<region><my server>/models/<my db>/refreshes GET https://<region><my server>/models/<my db>/refreshes/<run id>
  12. 12. ADF – Learning New Azure Data Factory self-paced hands-on lab for UI Orchestrating Big Data with Azure Data Factory V1 Learning path for Azure Data Factory V1 and V2
  13. 13. Q&A
  14. 14. Thank you for your time! Sergio Zenatti Filho Data & Analytics Architect sergiozenatti @ S ergioZenatti