Koen Verbeeck

Ready to take your SQL skills to the next level? With window functions, you can tackle complex problems in SQL with ease. Running totals? No issue. Removing duplicate values? Eazy peazy. Replacing cursors with a tally table? Donzo. Checking stock values for V-shapes? Okay, that one is a bit more complicated, but it can still be handled with window functions. In this session, we introduce you to the awesome world of window functions and explain how they can make your SQL life easier. We'll talk about the various use cases you can solve with them and how you can optimize their performance. At the end of the session, you'll have a solid grasp of window functions and know where you can use them in your SQL scripts. Basic SQL knowledge is assumed.

When you watch some conference sessions, or read some blog posts, it always seems like everyone is drowning in petabytes of (streaming) data. They're proclaiming you need the fastest, best, most scalable, distributed shared-nothing (or everything?) multi-parallel system that can also set coffee. But guess what? Not every company has to deal with a scale that businesses like Google, Amazon, or Tiktok have to deal with. Not every company needs streaming data with Kafka, Spark Streaming or Event Hubs. Not every company has complex unstructured data that you need to deal with in a data lake with tools like Databricks. Some companies have just a couple of gigabytes of data (or even less). Maybe a terabyte if we're pushing it. They don't need fancy streaming real-time dashboards, they just want to analyze their financial and sales data. It's ok if it just runs once a day. Their source systems are regular databases, maybe some Excel files and a SharePoint list. In this session, you're going to learn how you can build a data analytics platform in Azure that is dirt cheap. We're going to cover the following technologies and patterns: * cheap ingestion with Azure Data Factory using a metadata-driven framework, in combination with Azure Logic Apps and Azure Functions * a data warehouse implementation in Azure SQL Database. We'll cover design best practices and scaling options. * a Power BI model for presenting the data to the end users In each section, we'll look at how costs can be contained. After all, we want a data warehouse which doesn't cost more than €100 per month! It's assumed you have basic knowledge of Azure Data Factory, databases and SQL.

Is your database a bit slow? Do you regularly go for a cup of coffee because that query in SSMS is taking too long? This means you might need some Indexing Magic™ in your life! With Indexing Magic®, you too can speed up queries like you've never seen before! In this session, we'll guide you through the wonderful world of clustered indexes, index seeks, columnstore indexes and so much more. We'll explain why there important and what their impact can be on your database. We'll also explore how they are implemented in the various Microsoft SQL products, such as SQL Server, Azure SQL DB, Dedicated SQL Pool and Fabric. At the end of the session, you'll have a solid understanding of indexes and how you can use them to improve query performance. Basic SQL knowledge is assumed.

The gaps & islands problem is a common problem in data analysis. Some examples are: * how long are active periods that my server was running? Or, how long are the periods that the server was down? * on average, how long are the billable periods of my consultants? * what was the longest stretch of days without rain? In this session, you'll be introduced to the powerful concepts of window functions in T-SQL. With a practical use case, the gaps & islands problem is explained and solved. At the end of the session, you should feel confident in using window functions in your own data analyses. A basic understanding of T-SQL querying concepts is required to follow this session.

Often we need to find a way to uncover the hidden insights buried deep within the data jungles of the company. This can be a challenging task, but myths talk about the legendary Azure Data Explorer (ADX). Many claim it can handle even the most massive and complex data sets, as it's a brand new timeseries database in Azure. If you can handle the adventure, join our two explorers when they set out on a journey to discover the vast capabilities of ADX. We'll navigate through the setup and configuration of ADX like Indiana Jones did through ancient ruins. With their whip-like queries we'll uncover the powers of the Kusto Query Language (KQL) to solve our data puzzles. As we delve deeper into this data exploration, we'll find out that ADX is much more than a simple tool; it's like having a trusty sidekick by our side, helping us to navigate the treacherous waters of data analysis. With much adventure, we'll also unearth the link between ADX and Azure Cosmos DB. At the end of this ride, the audience will realize that with ADX on their side, they too can become daring data explorers. They will know when to use ADX and what its strengths and weaknesses are.

When building a data warehouse (DWH) in the Microsoft Data Platform stack, you typically have to write a fair share of T-SQL. Loading data into the data warehouse, transforming it into the desired format, troubleshooting and debugging, writing source queries for reports; all of those task require some T-SQL and preferably it's fast as well. In this session, we'll go over some T-SQL best practices from the viewpoint of the BI developer. We'll also cover indexing for the data warehouse and how you can make that SSRS report a bit faster. At the end, you'll walk out with solid knowledge on how to improve your T-SQL skills and deliver results faster. Most of this will also be directly transferable to other databases vendors. Basic knowledge of T-SQL and SQL Server is assumed.

Getting involved in the Data Platform community can be beneficial for your career, both short-term as long-term. Not everyone has the desire to jump on a stage and start speaking for an audience, but luckily you don't need to! There are many options available to build your personal brand out there. In this session, we'll go over these options and see how they can have a great impact on your profession live!

The era of cloud data warehousing has finally begun. Gone are the days where you had to provision expensive servers and spend days configuring and tweaking to get the technical details right. Using cloud infrastructure, we can skip past the technical set-up and start loading data immediately. Snowflake is a vendor offering a native cloud data warehouse, hosted on Azure. In this session, we'll introduce you to this new technology and explain the important concepts to get you started. Walking out of this session, you'll have all the knowledge you need to embark a project with Snowflake.

The era of cloud data warehousing has finally begun. Gone are the days where you had to provision expensive servers and spend days configuring and tweaking to get the technical details right. Using cloud infrastructure, we can skip past the technical set-up and start loading data immediately. Snowflake is a vendor offering a native cloud data warehouse, hosted on Azure. In this session, we'll introduce you to this new technology and explain the important concepts to get you started. Walking out of this session, you'll have all the knowledge you need to embark a project with Snowflake.