In this blog post, I will introduce two configuration-driven Azure Data Factory pipeline patterns I have used in my previous projects, including the Source-Sink pattern and the Key-Value pattern. The Source-Sink pattern is primarily used for parameterising and configuring the data movement activities, with the source location and sink location of the data movement configured in a … Continue reading Configuration-Driven Azure Data Factory Pipelines
Tag: Data Pipeline
Execute R Scripts from Azure Data Factory (V2) through Azure Batch Service
Introduction One requirement I have been recently working with is to run R scripts for some complex calculations in an ADF (V2) data processing pipeline. My first attempt is to run the R scripts using Azure Data Lake Analytics (ADLA) with R extension. However, two limitations of ADLA R extension stopped me from adopting this … Continue reading Execute R Scripts from Azure Data Factory (V2) through Azure Batch Service
SSIS in Azure #3 – Schedule and Monitor SSIS Package Execution using ADF V2
*The source code created for this blog post can be found here. In the previous blog posts in the SSIS in Azure series, we created a SSIS package to periodically ingests data from Azure SQL database to Azure Data Lake Store and deployed the package in the Azure-SSIS Integrated Runtime. Up to this point, we have … Continue reading SSIS in Azure #3 – Schedule and Monitor SSIS Package Execution using ADF V2
SSIS in Azure #2 – Deploy SSIS Packages to Azure-SSIS Integration Runtime in ADF V2
In the first blog post of the SSIS in Azure series, I gave a demonstration on how to create SSIS packages to move data in cloud, using a common use case that periodically ingests data from Azure SQL database to Azure Data Lake Store. In the pre-ADF V2 era, we can only deploy SSIS packages … Continue reading SSIS in Azure #2 – Deploy SSIS Packages to Azure-SSIS Integration Runtime in ADF V2
SSIS in Azure #1 – Periodically Ingesting Data from SQL Database into Azure Data Lake using SSIS
*The source code created for this blog post is located here. The low cost, schema-less and large column attributes of Azure Data Lake Store along with the large number of supported analytic engines (e.g., Azure Data Lake Analytics, Hive and Spark) makes it a prefect store-everything repository for enterprise data. We can offline the copies of business … Continue reading SSIS in Azure #1 – Periodically Ingesting Data from SQL Database into Azure Data Lake using SSIS
Data Ninjago (Financial Data Architecture) 
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