DATACON, a Microsoft Data Platform conference, brings together top experts, industry leaders, and data professionals for an immersive five-day experience. Focused on cutting-edge Microsoft data technologies—including Azure SQL Databases, Microsoft Fabric, SQL Server, and Real-Time Intelligence—DATACON delivers deep technical insights and practical solutions to help individuals and organizations unlock the full potential of their data.
With two days of intensive preconference workshops followed by three days of expert-led sessions, attendees gain hands-on experience and in-depth knowledge across a range of specialized tracks, including,&nbsp;Azure Data Services,&nbsp;SQL Server Optimization &amp; Best Practices,&nbsp;SQL Server Data Solutions for Enterprise,&nbsp;Data Warehousing,&nbsp;Data Integration &amp; Transformation,&nbsp;Power BI &amp; Data Visualization,&nbsp;Microsoft Fabric, and&nbsp;Data Security &amp; Governance.
At DATACON, learning comes from the best in the industry. Our speakers include Microsoft MVPs, Microsoft Certified Masters (MCMs), Microsoft Program Managers, Engineers, MCTs, and Regional Directors—each bringing expert-level insights into Azure SQL Databases, SQL Server, Purview, Power BI, Fabric, and more.
Choose a complete learning track to deepen your expertise or mix and match sessions to fit your organization’s specific needs. Whether you’re focused on building data pipelines, designing dashboards, integrating AI into your workflows, or mastering data governance,&nbsp;DATACON&nbsp;is your destination for actionable insights and transformative learning.

DATACON

Room 322

Finding the balance between cost, efficiency and performance for cloud-based ETL processes can be a tricky proposition, and a good ETL framework will help you get there. 

In this all-day session we will take a deep dive into what the components of such a framework may look like in Azure Data Factory, and why orchestration can be a good option if you're trying to minimize cost. We will also do an in-depth review of an actual framework I've developed and use today, which you can use as a starting point for your own efforts.

If you are currently using Azure Data Factory and feel like you're recreating the wheel all the time, or if you're planning to move from SSIS to ADF in the future and would like some ideas on how to create an ETL framework, this will be the perfect training day for you.

Deep Dive: Building a framework for orchestration in Azure Data Factory

Real-time Intelligence in Microsoft Fabric brings us into the next generation of data movement and event-driven architecture. As the arms race of cloud data platforms continues, make sure you know the weapons at your disposal so you and your company are fully equipped for the future - because the future is not far away. While you may be familiar with RTI’s streaming data capabilities, did you know it can be an integral part of your ETL architecture? While you may have heard of KQL, did you know it can do data visualization? While you may have heard of RTI, did you know it can help you monitor your entire data estate?
 
Join RTI product group members and Microsoft Data Platform MVPs for a full day of learning. Takeaways include:  
 
- Loading a full medallion architecture using RTI components 
- Use case by use case breakdown of the components of RTI and how customers are using them today across their data estate
- Data visualization and trend analysis with KQL
- Monitoring your entire data estate using Real-time Intelligence in Microsoft Fabric

ETL, KQL, and RTI: Harnessing Data in Motion with Microsoft Fabric

Copilot and other generative AI features bring new ways to transform and analyze data, generate insights, and create visualizations and reports in Microsoft Fabric and Power BI. Come see how to take advantage of Copilot in Fabric, what it can do and how to make sure it's enabled. 

Copilot in Fabric - AI Data Science Help Tips and Tricks

Discover the new SQL database in Microsoft Fabric, where seamless setup and an integrated development environment enable you to quickly leverage the power of an AI-driven data platform. Provision and deploy an autonomous database with built-in security in seconds, featuring automatic setup.
In this session, we'll delve into the potential of SQL database in Fabric, which combines the enterprise-scale features and capabilities of the Azure SQL Database engine with the autonomous management and ease-of-use advantages of the Microsoft Fabric data estate.
We'll uncover core functionalities, best practices, and real-world strategies to integrate your database with other Fabric workloads, creating a tailored, high-impact data stack that empowers your solutions to thrive within the Fabric ecosystem.

Accelerate Intelligent App Development with SQL Database in Microsoft Fabric

In this session, we will explore how to leverage Microsoft Fabric to create an end-to-end data solution. From leveraging Data Factory for data movement and orchestration, Notebooks to assist with data cleansing and further transformation, along with various engines such as Lakehouse and Power BI to complete the story. We look at how to get your data, get it into a usable form and possibly even reusing that data without having to copy with the end goal of providing reports and visualizations. We'll also look at other benefits where you can leverage the data for a complete solution.

Build an end-to-end data solution with Microsoft Fabric

Should you keep your data in the Fabric Lakehouse or the Warehouse? What are the pros and cons? In Fabric, all and any data is kept in the OneLake, and it is processed by one of the Fabric’s data engines. Choosing between Lakehouse and Warehouse (or both) is at the same time a strategic and performance impacting decision. •	In this demo oriented session you will learn:
o	Their distinctions and particular use cases
o	When they overlap
o	How to use them together
o	When not to use one of them (or either)

Fabric houses, when to go for Lakehouse or Warehouse (or both)?

Abstract:
Imagine your Dynamics 365 data not just as a record-keeping system, but as a live, actionable resource driving real-time decisions across your organization. In this session, we’ll dive deep into how Microsoft Fabric enhances Dynamics 365 with real-time intelligence, enabling you to unlock new opportunities for operational efficiency and innovation.
We’ll start by demonstrating how to implement event sourcing to capture and process changes in Dynamics 365 in a real time fashion way, integrating into Microsoft Fabric’s powerful analytics and data integration capabilities. Using real client success stories, you’ll see how these patterns enable instant updates, real-time reporting, and proactive decision-making.
You’ll also experience live demos showcasing the full lifecycle of real-time data integration—from capturing events in Dynamics 365 and transforming them in Fabric pipelines, to visualizing actionable insights in Power BI and bringing them back into Dataverse to empower your teams.

In this session you will learn how event sourcing and modern integration patterns bring data to life, through real client success stories and live demos.

What You’ll Learn:

	• How to set up real-time data pipelines between Dynamics 365 and Microsoft Fabric.
	• Practical event-sourcing patterns for building seamless, scalable integrations.
	• Techniques to surface actionable insights back into Dynamics 365 and Dataverse to empower decision-making.
	• Best practices for operationalizing real-time intelligence with minimal disruption to your existing architecture.

Why Attend:

You’ll leave this session with a step-by-step understanding of how to create real-time intelligence solutions, backed by practical examples and real-world use cases. Whether you're a data professional, architect, or Dynamics 365 expert, this session will give you actionable tools and insights to take back to your organization.

Post-Session Outcomes:

	• Start building your first real-time integration using Microsoft Fabric and Dynamics 365.
	• Access resources, templates, and best practices shared during the session to accelerate your implementation.
	• Connect with like-minded professionals to collaborate and share ideas.
	
Call to Action:

Don’t just learn—act! After the session, you’ll be encouraged to apply what you’ve seen, with resources and next steps to kickstart your real-time intelligence journey. Let’s turn your data into a strategic advantage!


Transform Your Business with Real-Time Intelligence: Microsoft Fabric Meets Dynamics 365

In this session, we will explore how Eventhouse is revolutionizing real-time intelligence through advanced dashboards and data exploration. As the demand for immediate insights and data-driven decisions grows, Eventhouse provides the tools and capabilities to meet these needs effectively. This session will cover the following key areas:

Introduction to Eventhouse:

Overview of Eventhouse and its role in real-time data processing.
Key features and capabilities that make Eventhouse a game-changer.
Implementing Real-Time Dashboards:

Setting up real-time data pipelines with Eventhouse.
Best practices for optimizing performance and scalability.
Ensuring data integrity and consistency in real-time environments.
Advanced Strategies for Data Exploration:

Leveraging Eventhouse for complex event processing.
Integrating IoT data, logs, and operational reports for real-time insights.
Case studies and real-world examples of successful implementations.
New Features and Enhancements:

Latest updates and enhancements in Eventhouse.
How to utilize new features for improved data processing and analytics.
Best Practices:

Proven methodologies for deploying Eventhouse in production.
Tips and tricks for maximizing the value of real-time data.
Ensuring security and compliance in real-time data processing.

Transforming Real-Time Intelligence with Microsoft Fabric

In the era of big data, the design of data processing architecture is crucial for efficient data management and analysis. This presentation explores the fundamental principles and considerations essential for constructing robust data processing systems. Key design principles such as scalability, reliability, security, and flexibility are examined in detail. 

The architecture's ability to handle varying data flows, ensure data integrity, and maintain security across multiple stages is emphasized. Additionally, the presentation discusses various architectural patterns, including data warehouses, data lakes, and data flow pipelines, highlighting their respective use cases and benefits.

Furthermore, the presentation contrasts traditional data processing architecture with the emerging concept of data mesh. While traditional architectures focus on centralized data processing and transformation, data mesh advocates for a decentralized approach, promoting domain-oriented data ownership and self-serve data infrastructure.

This comparison underscores the shift from monolithic data management to a more flexible and scalable architecture, addressing the diverse needs of modern data-driven organizations. 

By adhering to these principles and considerations, data engineers can create systems that not only meet current data processing needs but are also adaptable to future technological advancements and data requirements.

Data Processing Architecture: Key Design Principles & Considerations

What does the optimizer actually do with an index, what do the index structures look like, and what can e do to optimize index performance? This session covers index internals and optimizer limitations

Indexing for Performance

Data is a core part of our lives that influences all parts of business, from how we implement technology, to our establishment of business processes, all the way to individuals themselves. We solve tech and business process problems every day, but do we solve people problems?

How are people problems solved? With company culture. And culture can make or break data projects as easily as tech and process problems.

In this session, we'll talk about a company culture's influence on their ability to be data driven. We will identify common pitfalls that can influence how well your organization will be able to use data. We will also identify ways you can identify, and even measure, the data culture in your organization.

Building a Data Culture

If you work with data, you're generally dealing with two types of data: data in motion and data at rest. While we have many time-tested solutions for dealing with our data at rest, it hasn't been simple or straightforward to deal with data in motion - yet.

Real-Time Intelligence in Microsoft Fabric opens the door to some truly innovative, low-code approaches to dealing with your data in motion, whether that data is in ETL processes, streaming data, or something else entirely. Join me for this hands-on walkthrough to RTI - what it is, what it isn't, and what it can do for you.

Revolutionizing Data in Motion w/ Real-Time Intelligence in Microsoft Fabric

As data volumes and processing demands grow, traditional data engineering approaches face increasing challenges in scalability, performance, and cost efficiency. Microsoft Fabric’s Native Execution Engine is redefining the landscape by breaking away from JVM constraints, leveraging high-performance C++ execution, and seamlessly integrating with Apache Spark, Velox, and Gluten.

In this 70-minute session, we will explore how Fabric’s Native Engine optimizes SQL execution, accelerates ETL pipelines and live queries, and enhances real-time analytics across various data formats, diverse operators, and complex transformations. We’ll also analyze a few query execution patterns, demonstrating where the biggest performance gains can be achieved. 