SQLBits 2024
Slaying the Dataverse dragon with copilot
Two men versus dataverse.
If you have ever worked with PowerPlatform and Dataverse you will know it’s a bit of a dragon. Data goes in, but getting it out in a way that is simple for your data craftsman is not for the faint hearted.
We show you how to slay the dataverse dragon with your copilot sword; rescue your data -in-distress and take it to the promised land of SQL Azure and datalakes (which we call home)!
We talk about the various hard challenges of using Dataverse as your database, how we are solving these in the realworld on large Power Platform implementations containing Millions of records.
And how we’ve turned towards copilot to develop complex data integrations solutions in days rather than weeks/months.
If you were skeptical about the power of AI, this session will show you what’s possible with the right application.
Two men versus dataverse.
If you have ever worked with PowerPlatform and Dataverse you will know it’s a bit of a dragon. Data goes in, but getting it out in a way simply for your data craftsman is not for the faint hearted.
We show you how to slay the dataverse dragon with your copilot sword; rescue your data -in-distress and take it to the promised land of SQL Azure and datalakes (which we call home)! Sure, you have synapse-link but this is a one-size fits solution to a million different challenges we face as data folk.
- Fastest refresh is 15 minute intervals
- It always exports all fields, regardless of sensitivity and size
- It only exports to a datalake, there are no other targets
In this demo-led session, we talk about the various hard challenges of using Dataverse as your database, how we are solving these in the real world on large Power Platform implementations containing Millions of records.
And how we’ve turned towards copilot to develop complex data integrations solutions in days rather than weeks/months. In this case we show how we built it and the output.
This is a a metadata-driven solution that used CDC to extract data, apply transforms, load it into a data source via Azure Service Bus. The results speak for themselves.
If you were skeptical about the power of AI, this session will show you what’s possible with the right application.
If you have ever worked with PowerPlatform and Dataverse you will know it’s a bit of a dragon. Data goes in, but getting it out in a way simply for your data craftsman is not for the faint hearted.
We show you how to slay the dataverse dragon with your copilot sword; rescue your data -in-distress and take it to the promised land of SQL Azure and datalakes (which we call home)! Sure, you have synapse-link but this is a one-size fits solution to a million different challenges we face as data folk.
- Fastest refresh is 15 minute intervals
- It always exports all fields, regardless of sensitivity and size
- It only exports to a datalake, there are no other targets
In this demo-led session, we talk about the various hard challenges of using Dataverse as your database, how we are solving these in the real world on large Power Platform implementations containing Millions of records.
And how we’ve turned towards copilot to develop complex data integrations solutions in days rather than weeks/months. In this case we show how we built it and the output.
This is a a metadata-driven solution that used CDC to extract data, apply transforms, load it into a data source via Azure Service Bus. The results speak for themselves.
If you were skeptical about the power of AI, this session will show you what’s possible with the right application.
