Ben Weissman (he/him)

All the Azure Data offerings are great. But they are also confusing. Which one is right for you? Which size do you need? The answer is of course: It depends. Join us for a day of unmystifying the jungle of offerings! We will walk you through the different service offerings from SQL Server running in a VM over Azure SQL DB up to Fabric. To make sure, this is applicable and actionable, we will clearly structure this day by use cases for both, your needs to have your data land in azure as well as how to make it accessible for consumption: - HA/DR – are you intending to use Azure only as your backup datacenter? - Migration – is Azure going to be your new home? - ETL, Replication, Mirroring and Links – are you only intending to run some of your workloads, like analytics in the cloud and need to build a landing zone for your data from other sources? - Streaming - Are you getting data from sensors or other devices? - Analytics – Is fabric really your only choice to run reports in the future? This demo packed day will be your fast track to figure out which of the countless offerings is right for you and what it will take you to get there. We’ll focus on the technical aspects but also take a look at implications like security, governance and of course: cost.

Vector search is at the core of modern AI applications, powering recommendation engines, semantic search, and image recognition. Traditionally, implementing vector-based queries required adding a dedicated vector database, introducing complexity and additional infrastructure. But with SQL Server 2025, you can now store, query, and optimize vector embeddings natively - all within your existing environment, running entirely on-premises. Why does this matter? For organizations needing full control over their data, SQL Server 2025 enables AI-powered search without relying on external cloud services or third-party databases. In this demo-driven session, we'll start with how REST APIs are integrated into SQL Server 2025 as they are not only a cool feature on their own but also a prequisite to integrate AI into your workloads. We’ll keep going by looking at what vectors are, why they’re essential for AI applications, and how SQL Server 2025 simplifies vector search. You'll learn how to store and query vector embeddings efficiently, explore real-world scenarios like AI-powered recommendations and intelligent search, and discover best practices for indexing and optimizing performance. Of course, we’ll also take a look on what you’ll need to get going right away in your own environment! If you're looking for a way to integrate AI-powered search within your on-premises SQL Server - without external infrastructure - this is a session you won’t want to miss!

Join me, as we explore the capabilities of Azure Arc-enabled SQL Managed Instances. We will start with a quick introduction of Azure Arc-enabled Data Services: What are they and what do you need to deploy them? After that, we’ll focus on Azure Arc-enabled SQL Managed Instances and how they provide much more than just another SQL Server deployment, from evergreen versions through managed updates, peace of mind through managed backups and restores, flexibility through their pay as you go model and more! You will leave not only with a solid understanding of their capabilities but also the scripts and tools to deploy and manage Azure Arc-enabled SQL Managed Instances today!

Over the last years, Microsoft announced and released multiple services under their Azure Arc umbrella. But what's in it for you? Join me on a journey through the different offerings in Azure Arc and how they can benefit you as a data professional! While there are countless offerings, we'll mostly focus on those with a clear data focus: Azure Arc-enabled SQL Server, Azure Arc-enabled Data Services and Azure Arc-enabled Machine Learning. But Arc isn't the only hybrid puzzle piece: SQL Server 2022 also comes with a bunch of new hybrid features like Synapse Link or MI Link, so we'll take a look at those, too! You'll walk away from this demo loaded day with a good understanding on what Microsoft's hybrid offerings are and how they can benefit you as well as with pointers to more deep dive materials on the specific offerings!

With SQL Server 2019, Microsoft introduced a killer feature: Big Data Clusters. They bring advanced machine learning, an in-SQL Server Data Lake and enhanced Data virtualization through PolyBase. We will take a look at what that means, how Data Virtualization differs from Data Integration, what it takes to get a Big Data Cluster (even for small Data) deployed and how it can help you solve real time issues you may have. To do so, we will not only guide you through the product itself but also through the technologies and tools like Spark, Notebooks and Azure Data Studio that it relies on, so you can leave with a call to action on how you can leverage these new capabilities in your organization today!

Big Data Clusters are probably the biggest feature in SQL Server 2019. They provide additional AI, ML, Scale Out and Data virtualization capabilities. But what does that mean? We will take a deeper look at the extended Polybase options (Data Virtualization) as well as the option to integrate and query Big Data in SQL Server with the use of Kubernetes Clusters, Spark, Notebooks and more! This session covers all aspects of Big Data Clusters from deployment to the final big data solution.