It was a beautiful Saturday on May 31st in Redmond, Washington when over 600 people descended on the Microsoft Reactor Building to hear great speakers talking about Microsoft Fabric.

The speakers and attendees were great. The speakers made time for questions and the questions were asked and answered with heartfelt passion and conviction. The organizers were also treated to some extra hustle requirements when the total number of attends was more than twice than was expected a week before kickoff.

As a person who doesn't always spend most of their time in the world of "Data" I learned a lot more about one of the most exciting platforms that is not discussed enough. Everyone can rave about AI, but data is the blood that drives the beating hearts and data is often found everywhere.

This is why it was with great to learn about the expansion of data mirroring and the reach for Microsoft OneLake. Sources that many clients already own such as Microsoft Dataverse, Snowflake, Azure SQL and SQL Server on-premises (accessed using the Azure Data Gateway).

Other key technology advances were also shared.

Security continues to be a focus and enhanced security features have been added including the ability for more rich administration. This includes defining access permissions once and having them consistently applied in numerous places. 

There was also a significant amount of time spent on near Real-Time processing and productivity of queries. It was great to hear people taking performance seriously. In the past performance often becomes the forgotten stepchild that only gets considered when there is a problem or gets overlooked because of the advancement in hardware, but bottlenecks are not just hardware! 

Microsoft Fabric also includes Microsoft Azure Synapse Analytics and when I first started learning about and watching the use of Azure Synapse Analytics, I watched the deep, deep technical gurus climb the steep learning curve, so it was nice to hear that this learning curve is also being addressed. As some would say, the path to simplicity must first deep dive into the complexity. "Simple" is by far not the correct term, but as technology matures, grace and usefulness does get impacted by complexity, so leaning towards use and usability continues to be seen from the Microsoft development teams.

As an application focused resource, I continue to watch the new features that are related to business rules and as such the announcement that Microsoft Fabric now supports user data functions was an interesting one. To get "User Data Functions" summarized I asked for a little help (thank you ChatGPT) and here is what I found out "User Data Functions are reusable, parameterized functions that you define using T-SQL or Spark (PySpark/Scala) and then call from various components in Fabric. They encapsulate business rules, data transformations, or logic that you want to apply consistently across your data environment." so these have some very interesting potential.

and down the rabbit hole when I asked how UDFs related to or could be used with the Power Platform

"User Data Functions (UDFs) are a Microsoft Fabric feature and not native to the Power Platform, you can bridge them into Power Platform solutions—particularly when working with Power BI, Power Apps, or Power Automate that consume or manipulate data from Microsoft Fabric, OneLake, or Synapse Lakehouse."

One of the coolest benefits for companies working with the Microsoft Stack is that it is always pushing the bleeding edge and always offering mind bending options and notice that I have not even mentioned Microsoft Fabric and AI Foundry! 

"Fabric's data agents can now integrate with Azure AI Foundry via the Azure AI Agent Service"

In today's world of fast paced change and increasing reliance on data it is important to focus on the other side of complexity. Make sure your data is aligned and accessible using the least complex and yet highest quality solution.

Seamless integrations that are technically put into place with considerations such as. 

1) Is the data secure?

2) Is there quality and data review processes in place so that the data is clean and accurate?

3) Can you access the data at the desired speeds?

The Microsoft Stack of technologies continues to deepen and is sometimes hard to explain. Take for instance the "Common Data Universe", Dataverse. More than a Microsoft SQL Server database with layers and layers of role-based entitlement, external security tying deeply into the entire infrastructure using Entra (formerly Active Directory) and so many choices. Choices such as being able to split the database using Business Units which can significantly increase performance. 

If you take Dataverse and then consider that Azure extends the options, you end up with so many technically beautiful possibilities 

• Azure Data Factory: Ingest and transform data from Microsoft and non-Microsoft sources. Azure Data Factory is a managed cloud service that's built for complex hybrid and non-hybrid extract-transform-load (ETL), and data integration projects. Introduction to Azure Data Factory - Azure Data Factory | Microsoft Learn to read more.

• Azure Synapse Analytics: A bit of a learning curve for the technical folks (seen that first hand more than once), but Azure Synapse can be used to create a customer data lake and analyze large datasets.  "Azure Synapse brings together the best of SQL technologies used in enterprise data warehousing, Spark technologies used for big data, Data Explorer for log and time series analytics, Pipelines for data integration and ETL/ELT, and deep integration." retrieved from What is Azure Synapse Analytics? - Azure Synapse Analytics | Microsoft Learn What more do you need? 

ACCESS TO APIs, Of course! 

• Azure API Management: Securely expose data services. Azure API Management. "Azure API Management is made up of an API gateway, a management plane, and a developer portal, with features designed for different audiences in the API ecosystem. These components are Azure-hosted and fully managed by default." Azure API Management - Overview and key concepts | Microsoft Learn Not always required, but really good to know about as the technology options either are layered or are in parallel.