Azure Data Factory

What is the Azure Data Factory?

The Azure Data Factory is a managed service for data storage and processing.  It allows you to build cloud based solutions to move and store your data in a centralized managed environment.  Source data can be pulled from on premise or cloud environments consisting of structured, unstructured or semi-structured data.  Data is moved in the factory by a pipeline which is the basis of a workflow.  For example you could pull Customer data from the cloud and join it with on premise Customer Transaction data and have the workflow aggregate total customer sales and total product sales.  Then store the output in a table for use in business intelligence and analytics.

The Azure data factory offers a way to build your reporting environment outside the traditional ETL approach.  For the last 15+ years BI solutions involved processes that would extract only the data from source systems required to build the BI solution.  Then in the transformation step prep the data for loading into a data warehouse, typically a star or snowflake schema.  While this approach works to build a solution that meets the current requirements.  It is generally not flexible to answer questions that were not included in the original requirements.

By leveraging the data factory in an Extract and Load and Transform process (ELT).  You can create a data repository that stores as much of your data that you want in the format that best serves the data to users.  Once data is in the data factory you create transformations to build out solutions that meet your current requirements.  This could mean a star schema for an OLAP cube.  Or you could build summary and aggregate tables to store information that is consumed when needed.  If additional data is required by the users and it is already in the data factory.  There is no additional Extraction process required.

The Azure data factory could be a great addition to your BI environment.

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