Here are the previous 7 blog posts that I have completed in the series.ġ – Query Performance – Part 1 Migrating Azure Analysis Services to Power BI Premium Per User – Reporting/Analytics Made easy with FourMoo and Power BIĢ – Scalability – Part 2 Migrating AAS to PPU – Reporting/Analytics Made easy with FourMoo and Power BIģ – Data Loading – Part 3 | Migrating AAS to PPU – Reporting/Analytics Made easy with FourMoo and Power BIĤ- Incremental Refreshing – Part 4 – Migrating AAS to PPU – Reporting/Analytics Made easy with FourMoo and Power BIĥ- Historical Data Loading – Part 5 – Migrating AAS to PPU – Reporting/Analytics Made easy with FourMoo and Power BIĦ- Logging (Datasets, users & query performance) – Part 6 – Migration AAS to PPU – Reporting/Analytics Made easy with FourMoo and Power BIħ- Modelling – Part 7 | Migration from AAS to PPU – Reporting/Analytics Made easy with FourMoo and Power BI AAS – Deployments As well as adding or updating expressions, tables and potentially new columns. This is where the majority of my time will be spent is making deployment changes which could include adding or updating measures. Due to this fact when I am going to demonstrate below is when deploying changes or updates for AAS or PPU. There is a slight difference when deploying a project/dataset for the first time. In this blog post I will show the differences when completing a deployment from AAS and then PPU. Welcome to part 8, where in this blog post, I am going compare deploying datasets.įor those people who are not exactly sure what deployments are, what this means is when you are using Power BI Desktop and you click on Publish, you are effectively deploying your changes to the Power BI Service (Which could also be a server in the cloud).
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