These posts are about the Microsoft Data Platform, including SQL Server and Azure products and services. Topics include T-SQL, SQL Server Integration Services (SSIS), SQL Server Data Tools (SSDT), SQL Server Management Studio (SSMS), Azure Data Studio (ADS), Azure Data Factory (ADF), Azure Databricks, Azure SQL Databases, Azure SQL Data Warehouse and Azure Data Lake Storage.
In January 2019, I was honored to be asked to contribute to the PASS Insights BI Edition Newsletter. I said yes, of course! :) I chose to create an Azure Data Factory Data Flows introduction video. This is a sneak preview of the upcoming Data Flows feature, with a quick walkthrough of how easy it can be to create scalable data transformations in the cloud – without writing any code!
Please note: As of January 2019, when I recorded this video and published this blog post, Azure Data Factory Data Flows is still in preview. Features will be added and things will get changed, just like all the other Azure products. But! Hopefully this shows what you can look forward to.
At the end of this blog post, I have tried to answer some frequently asked questions about Azure Data Factory Data Flows.
About a month ago, I learned something new. I learned how to run SQL Server 2019 in Docker and how to set up my demo environment in a container. Cool stuff! I like whales. Whales are cool.
While learning, I started writing this blog post. Then I got distracted and never finished it. This weekend, I had to set up my demo environment again. It was the perfect opportunity to update the content and finally publish this post.
(Why did I have to set up everything again? Oh, it’s a long story that involves disk cleanup and a Cathrine who likes to delete things to keep her computer tidy. Ok, it’s not really a long story. It was more like “oops, I accidentally deleted my container”.)
Anyway! Back to the actual content.
In this post, I share my approach and code snippets for:
Getting SQL Server 2019
Running SQL Server 2019 in a Docker Container
Restoring Demo Databases (AdventureWorks and WideWorldImporters)
Last year at Microsoft Ignite, I was fortunate enough to interview Mike Flasko and Sanjay Krishnamurthi. This year, I got to have a follow-up chat with Mike Flasko and Sharon Lo! We talked about the recent and upcoming Azure Data Factory updates :)
In this interview, Mike and Sharon share the highlights from their session at Microsoft Ignite 2018. What are visual Data Flows? How are Azure Data Factory Data Flows different from the recently announced Power BI Dataflows? What’s on the Azure Data Factory roadmap? And finally, how can you provide feedback and get involved in private previews?
Azure Data Factory Updates with Mike Flasko and Sharon Lo
(I apologize for the unsteady video :( Unfortunately, I didn’t see how shaky it was until post-production. If it gets too distracting to watch, please just listen. Mike and Sharon share a lot of interesting things :) )
Thank you so much to Mike and Sharon for chatting with me on a busy day!
Earlier today, I ran into an interesting “feature” in the SQL Server Management Studio (SSMS) Results Grid.
During development, I found what appeared to be duplicate data. Uh-oh! I spent three hours debugging my query, looking into the underlying ETL, and doing all kinds of tests. I absolutely could not figure out what was wrong!
Then it hit me. Maybe my query was fine? Maybe the problem was how the results were displayed in the SSMS Results Grid? I tried expanding the columns. And sure enough. There it was. All my data, perfectly fine.
After facepalming, I started laughing. One of my Norwegian phrases is “erre mulig!?” It roughly translates into an exasperated, humorous “how on earth is that possible!?” I kept laughing. And of course, I had to tweet about my fail of the day: