Oskari Heikkinen
Data Analytics Architect at Datablinc
Helsinki, Finland
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Oskari has over a decade of experience in using Azure for data analytics at scale. He has been designing and implementing numerous projects for some of the largest companies in the Nordics. As a Microsoft Certified Trainer (MCT), Oskari conducts classes for subject-matter experts and consultants and provides external customer training sessions. He is also an active speaker at community events. Oskari has been honored with the Microsoft Most Valuable Professional (MVP) award in the Data Platform category six times. Additionally, he is certified as an Azure Solutions Architect, Fabric Analytics Engineer, and Azure Data Engineer.
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The love story of Analysis Services and Power BI
What is Azure Analysis Services and how does it differ from SQL Server Analysis Services? How is it related to Power BI? During this session I will introduce both of the services and help you to understand the fundamental relationship between the two. You will gain the knowledge of when and why should you use Analysis Services as a backbone for your Power BI reports. I will also do a couple of demos to show you how you actually can get started with both of these as well as which tools should you use while working with them.
Best Practices for building a Data Lake with Azure Databricks
Databricks is a Unified Analytics Platform making it easier than ever to do big data analytics on cloud. However, there are a lot of things you need to know and take into account before diving head first into a Data Lake. This session is intended for architects and developers who are looking to build a massive scale data storing and processing solution. I will go through the Best Practices for the purpose. In addition, I will demonstrate how to unify real-time and batch processing using Azure Databricks.
Introduction to Microsoft Fabric
Microsoft Fabric is the latest and greatest in cloud analytics, and at the moment of writing still in public preview. I will start from scratch to ensure you understand the basics and context. The aim is to unravel how this unified solution empowers you making it easier & faster than ever to harness data analytics.
During this session we will:
🔍 Delve into why Microsoft Fabric stands out among Microsoft cloud's data processing services.
🛠️ Learn how to leverage Fabric's developer-friendly features for rapid development and data insights.
💻 Get practical tips to kickstart your journey with this powerful analytics tool.
🚀 Embrace the future of data-driven decision-making with Fabric's cutting-edge capabilities.
This session is intended for architects and developers interested in crafting data-driven applications, architecting analytics solutions, or simply keen on staying ahead in the cloud landscape. This is your gateway to harnessing the full potential of Microsoft Fabric.
Warehouse in Microsoft Fabric: Architecture Deep Dive
Warehouse architecture includes VertiPaq, SQL Server Query Optimizer, and the new version of Polaris. How has Polaris evolved since Azure Synapse Analytics' Serverless SQL Pool? How has transaction support been added? What is V-ORDER's relevance to the Parquet file format, and how does it improve performance with VertiPaq? These functionalities will be demonstrated during the session, and you will gain a better understanding of how the Warehouse works under the hood.
This talk is intended for architects and developers. Join this session to ensure you're using the technology optimally or to avoid the common pitfalls if you're just getting started.
Best Practices for Fabric Eventhouse
Eventhouse is a distributed query processing technology in Microsoft Fabric. In this session, we will deep dive into the relevant technical details to understand how it delivers the incredible performance. The session will build on that information and also deliver the Best Practices. Demos are included to show how some of the Best Practices can be implemented.
This talk is intended for architects and developers. Join this session to ensure you're using the technology in an optimal way or to avoid the common pitfalls if you're just getting started.
User Data Functions: Development, Testing, and Integration
User Data Functions (UDFs) enable extending capabilities with custom Python logic hosted in Microsoft Fabric. When should you consider using one? What is the best way to develop, test, and debug the solution? How to install custom libraries? What options do we have for triggering the execution? I will answer all of these questions during this session.
I will also demonstrate how to run and debug a UDF locally before publishing it to Microsoft Fabric. In addition, I will show how to trigger a UDF with a REST API call and from a Power BI report, as well as various ways to use existing data in a semantic model and/or new data as input for the UDF.
This talk is intended for data architects, developers, and analysts. Join this session to learn when to use UDFs and how to develop your solution using an optimal approach. I will also list the recommended tools and libraries required for those just getting started.
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