Organizations need to have the ability to explore their critical business data for data preparation and wrangling in order to provide accurate analysis of complex data that continues to grow every day. Data preparation is required so that organizations can use the data in various business processes and reduce the time to value. Data Factory empowers you with code-free data preparation at cloud scale iteratively using Power Query. Data Factory integrates with Power Query Online and makes Power Query M functions available as a pipeline activity. Data Factory translates M generated by the Power Query Online Mashup Editor into spark code for cloud scale execution by translating M into Azure Data Factory Data Flows. Wrangling data with Power Query and data flows are especially useful for data engineers or 'citizen data integrators'. Data wrangling in data factory allows you to build interactive Power Query mash-ups natively in ADF and then execute those at scale inside of an ADF pipeline. 00:00 Introduction - Agenda of Demo 01:55 Create Azure Data Factory 03:45 Create Power Query Activity 05:00 Power Query Mashup Editor 09:15 M Query 12:25 Create Pipeline with Power Query Activity 13:40 Run Pipeline 14:00 Monitor Pipeline
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