Erwin de Kreuk
Data Platform MVP | Lead Data and AI |Public Speaker | InSpark | Innovate to Accelerate
Rotterdam, The Netherlands
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Erwin de Kreuk is a passionate and very experienced Microsoft Solution Architect.
Working as a Principal Consultant/ Lead Data and AI for InSpark in the Netherlands. Speaking at different national and international data community events. He is been awarded as Data Platform MVP.
He is working in the world of data on the Microsoft Platform for last 14 years and the last 6 years he has shifted his focus to the Azure Platform.
Answering complex customer cases and technical issues are part of his day-to-day work. In addition to this work, he is a member of the Technology Board within InSpark and leads a team of highly experienced Data Expert in the field of Microsoft Data Platform.
He is eager in helping out customers in getting the most added value out of their complex Analytics environment with a strong focus on solutions in the Azure Cloud (Platform as a Service) and Microsoft Fabric
As a Technology Board member, he is always investigating the latest (vs newest) possibilities/opportunities and sharing his enthusiasm among his colleagues, the community and customers. He is one of the main Stakeholders for the InSpark Solution (Managed) Oxygen, a Modern Data platform Estate as-a-service.
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Expand your Fabric environment with Microsoft Fabric Workloads
In today's dynamic landscape, where agility and scalability are paramount, Microsoft Fabric stands out as a powerful platform for building and managing distributed applications. In this comprehensive session, we'll delve into the intricacies of expanding your Fabric environment by seamlessly integrating Microsoft Fabric Workloads.
The versatility of workloads allows you a wide range of possibilities, enabling you to create solutions that are perfectly suited to your operational requirements.
During the session we will guide you:
• How you can create your first workload and integrate the workload in Fabric.
• How the Fabric workloads integrate with Microsoft Entra ID
• How the Fabric Permission model works
Whether you're a developer, architect, or IT professional, you'll discover practical strategies for expanding and scaling your applications within the Fabric ecosystem. From native integration techniques to best practices, we'll cover it all. Join us as we unravel the intricacies of Fabric and empower your applications to thrive.
Data Governance in the Era of AI
Data is the fuel for digital transformation, but it also poses many challenges for organizations that need to manage, protect, and monitor their sensitive information. How can you ensure that your data is trustworthy, compliant, and secure across your entire data estate? How can you empower your data users to access and analyze the data they need without compromising data quality and governance?
In this workshop, you will learn how Microsoft Fabric, a unified data platform that enables data-driven insights and actions, can help you address these challenges with its built-in governance and compliance capabilities. You will also learn how Microsoft Purview, a comprehensive data governance service, can work seamlessly with Microsoft Fabric to provide end-to-end data governance across your hybrid and multi-cloud environments.
By the end of this workshop, you will be able to:
- Understand the basic building blocks of Microsoft Fabric governance and compliance, such as endorsement, metadata scanning, and lineage.
- Use Microsoft Purview to discover, classify, and protect your Fabric data using sensitivity labels and policies.
- Use Microsoft Purview to create an up-to-date map of your entire data estate that includes data classification and end-to-end lineage.
- Use Microsoft Purview to monitor and report on the activities and compliance status of your Fabric data.
This workshop is designed for data professionals, business analysts, and IT administrators who want to learn how to leverage Microsoft Fabric and Microsoft Purview to govern their data estate effectively and responsibly. To participate in this workshop, you will need a Microsoft Fabric account and a Microsoft Purview account. You will also need basic familiarity with Microsoft Fabric and Microsoft Purview concepts and features.
Embark on a transformative journey into building an end-to-end solution within the Microsoft Fabric.
As a newcomer, you’re about to dive into the fascinating process of data extraction and report creation.
This session will guide you through the essential steps to kickstart your data extraction endeavors. You’ll gain a deep understanding of diverse data sources and learn to navigate through powerful connectors within Microsoft Fabric, setting up a solid foundation for your data journey from all the lessons we have learned.
Immerse yourself in the realm of Data Factory, where you’ll craft seamless data pipelines and Notebooks that effortlessly shuttle information between sources.
But the journey doesn't stop there. You'll also learn to take full advantage of on demand loading and (near-) real-time reporting capabilities by using Direct Lake connectivity to Power BI.
And the last part of the journey, whilst we're working in the era of AI, we take full advantage of services like Co-pilot to support our development process throughout the entire journey up to data visualization.
This session is more than just an introduction to Microsoft Fabric. It’s a comprehensive guide designed to equip you with the knowledge and confidence to navigate the landscape of data extraction and report creation.
So, get ready to unravel the mysteries of data extraction and chart your course towards building insightful reports. Welcome to your immersive Fabric initiation.
Microsoft Fabric: Building a Data Ingestion and Processing framework to Drive Efficiency
Data pipelines are essential for moving and transforming data between different systems. However, managing a large number of data pipelines can be challenging and time-consuming. How can you ensure that your data pipelines are efficient, reliable, and consistent?
In this session, you will learn how to use a metadata-driven approach to manage your data pipelines and Notebook in Microsoft Fabric. Metadata is data about data, such as source, destination, schema and format.
By using metadata to define and control your data pipelines, you can achieve the following benefits:
1. Simplify and automate the creation and execution of data pipelines
2. Optimize the performance and scalability of data pipelines
3. Monitor and troubleshoot data pipelines
We will show you how to implement a Data Ingestion and Processing framework based on the Medallion Lakehouse architecture. We will also share the key learnings, best practices, and patterns that we have discovered from applying this framework in our own work.
All code used during the demo will be shared afterwards, so you can start building a framework directly after the session
Get started with a medallion architecture in Microsoft Fabric
Microsoft Fabric is an all-in-one analytics solution that enables you to build and manage lakehouses, data warehouses, and data integration pipelines with ease and efficiency. In this session, you will learn how to use the medallion architecture design to organize and transform your data across bronze, silver, and gold layers of a lakehouse for optimized analytics. You will also learn how to connect to your lakehouse using SQL endpoints and Power BI, and how to ensure the security and governance of your data. By the end of this session, you will have a solid understanding of the benefits and best practices of using the medallion architecture in Microsoft Fabric.
Leveraging Microsoft Fabric in Your Azure Data Solutions
Microsoft Fabric is a new platform that enables you to connect, transform, and analyze data from various sources and services. In this session, you will learn how to integrate Fabric with your existing Azure data solutions, such as Azure Data Factory, Azure Synapse Analytics, and Azure Databricks. You will discover how Fabric can enhance your data capabilities and performance, as well as how to use Fabric components and services to create end-to-end data scenarios. This session is designed for anyone who wants to learn how to use Microsoft Fabric in their Azure data ecosystem.
Navigating Data Governance in Microsoft Fabric and Purview
Embark on a high-flying data governance adventure with Wolfgang, an Austrian data governance expert, and Erwin, a Dutch data stewardship virtuoso. In this aviation-themed session, participants will explore the dynamic landscape of data governance within Microsoft Fabric and Microsoft Purview.
Tailored for beginners, this session will cover the foundational principles of data governance, providing a solid framework for effective implementation. Attendees will be taken on an interactive tour, leveraging demo movies to gain practical insights into harnessing the capabilities of Microsoft Fabric and Purview.
Wolfgang and Erwin will guide participants through strategies for seamless data governance operations, ensuring compliance and security while optimizing workflows. Special attention will be given to the complexities of international data governance, enabling participants to navigate global data landscapes with confidence.
Whether you're a novice or seasoned professional, this 100-minute journey promises a turbulence-free introduction to data governance. Fasten your seat belts for a session packed with actionable insights, empowering you to chart a clear course for data governance success.
Real-Time Analytics in Microsoft Fabric, a real game changer?
In today's fast-paced business landscape, real-time analytics have become indispensable for organizations that want to stay ahead of the competition. By enabling instant access to up-to-date information and enabling data-driven decision-making, real-time analytics are proving critical in a variety of industries and scenarios, from manufacturing operations to cybersecurity and beyond. Microsoft Fabric offers a comprehensive set of tools and services that facilitate the development of robust real-time analytics capabilities.
Join this session and dive into the world of real-time analytics with Microsoft Fabric. Learn how to build an Eventstream through a step-by-step approach, capturing and processing data as it happens for reporting and decision-making purposes. Understand the key features and functionality of Microsoft Fabric, including real-time data processing, advanced analytics, flexible visualizations, and custom alerts. Learn how real-time analytics can revolutionize IoT analytics, telemetry data analytics, human and system log investigation, and more.
Whether you are an date engineer, a data analyst or a business decision maker, this session will provide valuable insights
Onelake with Fabric, The Data Lake-as-a-Service Platform
In this session, we delve deeper into OneLake, a crucial component of Microsoft Fabric that serves as a data lake-as-a-service solution. OneLake enables organizations to avoid data silos and centrally store and manage data without the need to build or maintain a data lake themselves. It functions as a data storage platform, much like OneDrive does for files.
During this session, we explore how OneLake works and why it is a true game changer. We discuss the various capabilities of OneLake, including out-of-the-box governance features such as data lineage, data protection, certification, and catalog integration. These features facilitate streamlined data management and enhanced compliance.
Furthermore, we examine the integration of OneLake with other services, such as Power BI. Discover how applying a sensitivity label to a OneLake file automatically applies to related Power BI datasets, ensuring consistent security and compliance.
Whether you're a data engineer, data scientist, or analyst, this session provides valuable insights into how OneLake can help centralize and manage data while leveraging the scalability, security, and advanced capabilities of Microsoft Fabric. Get ready to explore the possibilities of OneLake and understand why it is a critical component of the modern data landscape.
I look forward to welcoming you to this engaging session, and learn you how OneLake can make a difference in your organization.
Securing Azure Synapse: Best Practices for Data Protection, Compliance, and Performance
Discover the essential steps to build a secure Azure Synapse Solution in today's data-driven world. This session provides comprehensive knowledge and practical guidance on implementing robust security measures, including the Cloud Adoption Framework (CAF), Well-Architected Framework (WAF), Data Exfiltration Protection, (Managed) Private Endpoints, and secure connections.
During this session, you will:
• Learn how to implement a secure and compliant Azure Synapse Solution within the Cloud Adoption Framework (CAF) and its core components.
• Delve into the five pillars of the Well-Architected Framework, understanding how to apply them to Azure Synapse Solution for enhanced security, reliability, performance, and cost optimization.
• Gain techniques to implement data exfiltration protection measures, including access controls, data classification, and auditing, safeguarding your sensitive data from unauthorized extraction.
• Discover the benefits of (Managed) Private Endpoints and learn how to establish secure connections between your Azure Synapse workspace and data sources.
• Learn various methods to secure connections, including Azure Virtual Network (VNet) service endpoints, Azure Private Link, and SSL/TLS encryption, necessary for a building a secure Azure Synapse Solution
• Experience a mix of slides, demos, and hands-on exercises throughout the session.
By the end of the session, you will have a solid understanding of how to build a secure Azure Synapse solution, integrating CAF, well-designed framework, data exfiltration protection, (managed) private endpoints, and secure connections. You will be equipped with actionable insights to ensure the security and compliance of your Azure Synapse workloads, effectively protecting your data.
Note: This session assumes a basic understanding of Azure Synapse Analytics and cloud services.
How to govern the Microsoft Intelligent Data Platform
So you have heard about the Microsoft Intelligent Data Platform, which includes Azure Synapse Analytics, Power BI, and Microsoft Purview and started making your first experiences with it?
Then it is time we talk about the importance of data governance, data classification, and data labeling to maintain data security and compliance.
In this full-day workshop, you will learn how protect your sensitive data in reports and dashboards using techniques like sensitivity labels in Azure Synapse Analytics or labels, policies, and rules in Power BI. We will also walk through the steps required to extend your Power BI Lineage with Lineage from your sources with the help of Purview and Synapse Analytics.
In addition, we will cover setting up access controls and permissions to ensure that only authorized users can access sensitive data.
We will have a good mix of slides, demos and hands-on exercise, allowing you to apply what you have learned using the Microsoft Intelligent Data Platform!
Provision users and groups from Azure Active Directory to Azure Databricks
This session will cover provisioning users and groups from Azure Active Directory (AAD) to Azure Databricks using System for Cross-domain Identity Management (SCIM).
The session will include an overview of SCIM and its integration with Azure Databricks, as well as a walkthrough of the steps to provision users and groups using SCIM. Topics such as user and group mappings, SCIM configuration, and user and group management options will also be discussed.
We will also discuss the different options for managing user and group identities in Azure Databricks, including how to handle user and group provisioning, deprovisioning, and updates.
By the end of this session, attendees will have a comprehensive understanding on how to provision users and groups from AAD to Azure Databricks using SCIM, and how to manage user and group identities in a scalable and secure manner in the cloud.
Extending Power BI governance with Microsoft Purview
In this deep dive session, we will explore how Power BI and Microsoft Purview can work together to provide a comprehensive data governance and analytics solution. We will start by discussing the key features of each platform and how they complement each other, but also make sure where they differ from each other
Next, we will dive into real-world examples of how Power BI and Purview can be used together to gain insights from data. This will include using Purview to discover, classify, and catalog data sources. But before you can scan your Power BI tenant, we will learn you how to setup these scans within your tenant but also in a cross-tenant situation.
We will also discuss best practices and the do's and don'ts for integrating Power BI and Purview into your organization's data governance strategy, including considerations for data security and compliance.
You will learn how you can extend your Power BI Lineage with Lineage from your sources with the help of Purview.
By the end of this session, you will have a clear understanding of how Power BI and Purview can be used together to drive data-driven decision making in your organization.
Designing and managing a cost-effective data platform in Azure Synapse Analytics
Azure Synapse Analytics is a powerful data platform, but it can also be expensive if you don't know what you're doing. In this session, we will go through the different components of Azure Synapse Analytics and discuss how to design a cost-effective data platform.
We will cover topics such as choosing the right pricing tier, optimizing data storage and processing, and leveraging built-in cost management features. We will also discuss how to optimize your data platform for cost efficiency by using features such as serverless compute, pre purchase compute and reserved capacity.
Attendees will leave with a better understanding of how to design and manage their Azure Synapse Analytics platform for cost efficiency and how to design a cost-effective data platform that meets your organization's needs.
Topics we will cover:
- Pricing Models for compute Resources in Azure Synapse Analytics
- Storage Types and Tiers
- Pricing Models
- Optimizing Cost with Resource-Scaling
- Using serverless compute and reserved capacity options for cost savings
Unleashing the Potential of Metadata-Driven ELT Framework
A metadata-driven ELT framework in Azure Synapse Analytics or in Microsoft Fabric is a way of organizing, optimizing and managing data pipelines that involves using metadata to define and control the flow of data from source to destination. This can be useful for organizations that have a large number of data pipelines and want to have more control over how data is processed and moved between systems.
In this session, we will discuss the benefits of using a metadata-driven approach to managing data pipelines. Our discussion will include practical examples and best practices for implementing a metadata-driven ELT framework in your organization based on the Medallion Lakehouse architecture. We will also provide you with code samples and walk them through how to get started with implementing this framework in your own work.
This session is ideal for data engineers and other technical professionals who want to learn how to optimize their data pipelines in Azure Synapse Analytics or Fabric. By the end of the session, you will have a clear understanding of how to use a metadata-driven approach to manage and maintain data pipelines, enabling better control and visibility over their data processes.
Create an Azure Synapse Lake Database without writing code
So, I don't have to write any code to build up my facts and dimensions, yes you have read that correctly.
Within Azure Synapse Analytics, a new functionality/tool is available, the map data tool. The map data tool allows you to easily map your Data from a source into the target tables in the Synapse Lake Database.
Map Data is a guided experience where you can generate a mapping data flow without having to start from a blank canvas. Once you have created the mappings then you can easily generate a scalable mapping data flow in a Synapse Pipeline.
After you have published the Synapse Pipelines, you can run these Pipelines and then visualize your generated data model in Power BI? Sounds great or not?
I will show you how the map data tool works and how to visualize the data in Power BI afterwards in a step-by-step demo-based session. After this session you will have the knowledge to build and visualize your first Synapse Lake Database.
Streamline Data Governance with Microsoft Purview
In this session, I will give you a Comprehensive Overview of Microsoft Purview, a unified data governance solution designed to help organizations manage their data more effectively.
Data governance is critical to any organization's data strategy as it ensures data quality, security, and compliance. However, it can be a complex process, especially when managing large volumes of data across various systems and platforms.
During this session, we will be discussing the key features of Microsoft Purview, including data discovery and classification, data cataloging and management, and data lineage and mapping. We will also explore how Purview integrates with other Azure services such as Azure Synapse Analytics, Azure Data Factory, and Azure Databricks to enable end-to-end data governance.
This session is perfect for data professionals, architects, and CDO's who want to learn more about how Purview can help them overcome their data governance challenges.
By the end of the session, you will have a clear understanding of how Purview can streamline data governance and enhance data quality, which will ultimately lead to better decision-making and collaboration within their organizations.
Microsoft Purview what does this mean to me as an organization?
Microsoft Purview offers significant benefits for business users, streamlining and enhancing data governance, compliance, and risk management.
In this session, we will cover the new portal specifically designed for data governance, which includes functionalities for:
• Business Domain Management: Organize and manage data assets by business domains, ensuring relevance and context.
• Data Products: Create, manage, and govern data products, ensuring they meet organizational standards and are easily discoverable.
• Data Quality Management: Tools to assess and improve data quality, ensuring reliable and accurate data.
• Data Estate Health: Monitor the overall health of your data estate, identifying issues and areas for improvement.
By the end of the session, you will have a comprehensive understanding of how Microsoft Purview can enhance your organization's data governance what Microsoft Purview could mean in your organization.
Get control of your Azure Synapse environment, define your access control the right way today!
Azure Synapse Analytics is Microsoft's analytical engine that brings together data integration, enterprise data warehousing, and big data analytics.
As we now take a more holistic approach, more different types of user groups will use the platform. The more important the setup of an authorization matrix in advance will be. The following topics will be covered during this session:
• What Azure AD roles do we need to deploy an Azure Synapse Workspace?
• How can we simplify access control by using security groups that are aligned with people's job roles.
• How do we handle different user personas in Azure Synapse Analytics? For example, what is a Data Scientist or Data Engineer allowed to do and what not?
What access control settings do we need to have to:
• Store code in Azure Devops
• Debug a pipeline
• Run a Notebook
During this session I would like to take you through some practical examples on how you can set up these roles for your Azure Synapse in order to get in to control of your environment.
Scale your SQL Pool dynamically in Azure Synapse
In this Lightning talk I explain how can you scale up or down your SQL Pool in Azure Synapse Analytics using an Synapse Pipeline. An easy way so save some cost in your Analytics Environment
Getting started with building your Azure Synapse environment
In this session, we will explore how to create an Azure Synapse environment, step by step. Azure Synapse Analytics is a cloud-based analytics service that brings together big data and data warehousing. It offers a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs.
During this session, I will cover the pre-requisites necessary for creating an Azure Synapse environment. You will be guided through the steps to create an Azure Synapse Workspace and to create Synapse SQL, Serverless and Spark pools for data processing and ingestion. We'll also explore the various methods for loading data into Synapse.
Finally, I will demonstrate how you easily can query your data.
By the end of this session, you will have a clear understanding of how to create an Azure Synapse environment, load data into it, and query the data efficiently.
The Crucial Role of Data Quality in Your Data Estate
In today’s data-driven landscape, the quality of your data directly impacts the accuracy of AI-driven insights and decision-making. Here’s why data quality matters:
- Trustworthy Insights: Reliable data ensures that AI models generate accurate predictions and recommendations. Without trustworthy data, there’s a risk of eroding trust in AI systems.
- Business Processes and Decision-Making: Poor data quality or incompatible data structures can hinder business processes and decision-making capabilities. Clean, well-structured data is essential for informed choices.
A powerful data platform plays a crucial role in maintaining high data quality. With a robust data platform, you can ensure that your data is consistent, accurate, and readily available for various applications and processes. Leveraging such a platform is foundational for implementing effective data quality measures.
During the session, we will guide you through Microsoft Purview Data Quality:
This comprehensive solution empowers business domain and data owners to assess and oversee data quality. It offers no-code/low-code rules, including out-of-the-box (OOB) and AI-generated rules.
Purview Data Quality incorporates AI-powered data profiling. It recommends columns for profiling, allowing human intervention to refine these recommendations. This iterative process enhances accuracy and improves underlying AI models.
By integrating Microsoft Purview with your data platform, you can apply and monitor data quality processes more effectively. This integration ensures seamless data management and governance across your data estate.
During the session, we will walk you through the Data Quality Life Cycle:
- Assign data quality steward permissions in your data catalog.
- Register and scan data sources in Microsoft Purview Data Map.
- Set up data source connections for quality assessment.
- Configure and run data profiling.
- Define and apply data quality rules.
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Erwin de Kreuk
Data Platform MVP | Lead Data and AI |Public Speaker | InSpark | Innovate to Accelerate
Rotterdam, The Netherlands
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