Presentation topics

Throughout his career, Rick van der Lans has delivered a diverse array of high-impact seminars, webinars, and keynote presentations at many of the world's most respected industry conferences. His dynamic and insightful speaking style, combined with deep subject-matter expertise, has made him a sought-after voice in the fields of data management, business intelligence, and analytics.

His speaking engagements attract audiences ranging from data practitioners and IT professionals to business executives and strategic decision-makers. Whether delivered in-person or online, his presentations consistently receive high praise for their clarity, depth, and practical relevance.
In addition to public conferences, he frequently delivers tailored seminars, keynote addresses, and in-house training sessions to meet the specific needs of various audiences.
For many years, he served as the esteemed chairman of two of Europe’s leading data-focused events: the annual European Enterprise Data and Business Intelligence Conference in London, and the Data Warehousing and Business Intelligence Summit held annually in The Netherlands. In these roles, he not only guided the direction of the events but also played a key part in shaping conversations around emerging trends, technologies, and best practices in the data space.

Rick F. van der Lans offers presentations on the following topics, available in the form of concise keynotes, in-depth seminars, or hands-on workshops (these presentations can all be delivered in Dutch):

Practical Guidelines for Designing Modern Data Architectures

This session delivers practical guidance, expert tips, and essential design principles to help address the key challenges in building modern data architectures. Designed for data architects and BI professionals, the session emphasizes how to create scalable, flexible, and future-ready data environments that support diverse analytical needs.
Participants will explore foundational and emerging concepts, including data lakes for versatile storage, big data processing frameworks, Data Vault for agile data modeling, and cloud computing for scalable infrastructure. The session also delves into technologies such as data virtualization for real-time access, NoSQL for unstructured and high-volume data, Hadoop for distributed computing, and data warehouse automation to accelerate delivery and reduce complexity.

By integrating these tools and approaches, attendees will gain a clear roadmap for designing modern data architectures that effectively bridge traditional systems with cutting-edge technologies.

For more information on this session click here.

The Logical Data Warehouse - Design, Architecture, and Technology

This session provides an in-depth exploration of the logical data warehouse architecture—a modern approach designed to meet the evolving demands of business intelligence (BI) in today’s data-driven environment. Unlike traditional architectures, the logical data warehouse introduces a paradigm shift by decoupling data producers (such as source systems and data pipelines) from data consumers (such as analytical tools, dashboards, and reporting services).
This architectural separation fosters greater modularity, enabling individual components of the BI ecosystem to evolve independently. It also enhances scalability, allowing organizations to efficiently manage growing volumes, varieties, and velocities of data. Furthermore, the logical data warehouse supports increased agility by facilitating faster adaptation to changing business requirements and technology advancements.

By abstracting data access and delivery from underlying storage and processing mechanisms, this architecture enables seamless integration with modern data platforms, including cloud-based storage, data lakes, real-time processing engines, and big data frameworks. As a result, organizations can more effectively operationalize advanced analytics, machine learning, and other data-intensive initiatives without being constrained by rigid infrastructure.

For more information on this session click here.

Introduction to Data Virtualization: Technology and Use Cases

This session explores data virtualization; an agile, modern approach to integrating data across diverse systems without physically moving it. Participants will learn how data virtualization enables real-time, unified access to data from databases, cloud services, big data platforms, and more, significantly reducing complexity and accelerating analytics.

The session covers the core benefits and features of data virtualization, compares leading tools and technologies, and presents real-world use cases to demonstrate its value in enabling self-service BI, enterprise reporting, and operational decision-making.
Additionally, the seminar examines how data virtualization supports broader initiatives such as Master Data Management (MDM), Data Governance, and the Internet of Things (IoT), highlighting its role in building flexible, scalable, and responsive data architectures.

For more information on this session click here.

Incorporating Big Data, Hadoop, and NoSQL in Business Intelligence Systems and Data Warehouses

The emergence of technologies such as big data platforms, Hadoop, NoSQL databases, Apache Spark, and Kafka has significantly expanded the toolkit for building modern business intelligence (BI) and data warehouse solutions. These technologies offer powerful capabilities that enable the development of more flexible, scalable, and high-performance BI environments.

However, with so many options available, organizations are often faced with the critical questions: Which technologies should be adopted? And in which use cases do they provide the most value?

This session provides a structured exploration of how to effectively integrate big data technologies—such as Hadoop and NoSQL—into existing BI and data warehouse architectures. It examines their strengths, ideal application areas, and how they can complement or extend traditional systems to support advanced analytics, real-time processing, and large-scale data integration.

For more information on this session click here.

Modern Data Warehouse Architectures

Today’s data warehouse architects face a rapidly evolving landscape filled with critical design decisions. Should the data warehouse be built using modern frameworks like Hadoop and Spark? Are data marts still relevant in this new context? What are the implications of adopting Data Vault modeling for warehouse design? And how do emerging trends like data streaming and the Internet of Things (IoT) integrate into the architecture?

This session on modern data warehouse architectures provides a comprehensive overview of the latest architectural approaches and innovations. It examines how traditional principles are being redefined to accommodate new technologies, data sources, and business requirements. Participants will gain a clear understanding of the options available and how to make informed choices that align with their organization's needs and long-term data strategy.

For more information on this session click here.