{"id":61742,"date":"2021-06-14T10:00:01","date_gmt":"2021-06-14T18:00:01","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/devops\/?p=61742"},"modified":"2021-05-21T10:02:46","modified_gmt":"2021-05-21T18:02:46","slug":"azurefunbytes-intro-to-azure-data-factory-with-kromerbigdata","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/devops\/azurefunbytes-intro-to-azure-data-factory-with-kromerbigdata\/","title":{"rendered":"AzureFunBytes – Intro to Azure Data Factory with @KromerBigData"},"content":{"rendered":"

AzureFunBytes is a weekly opportunity to learn more about the fundamentals and foundations that make up Azure. It’s a chance for me to understand more about what people across the Azure organization do and how they do it. Every week we get together at 11 AM Pacific on Microsoft LearnTV<\/a> and learn more about Azure.<\/p>\n

\"AzureFunBytes<\/p>\n

Data drives so many of our decisions. Whether it’s determining which products to have viewed first in our online retail store, or creating reports for business intelligence, we’ve got so much data! It’s time to figure out how to learn how to take that data and provide human-readable information that will help us continue to make the right decisions.<\/p>\n

This week on AzureFunBytes, I am joined by Principal Program Manager, Mark Kromer<\/a> about how to store and process our big data with Azure Data Factory. Mark will discuss the ETL (Extract, Transform, Load)<\/a> process that gets our data into Azure Data Factory<\/a>. I ask Mark how can we transfer the data we might have to Azure<\/a>? We look into how to create pipelines to automate the ingestion of our data from various data stores.<\/p>\n