This seminar explores the strategic implementation of Knowledge Graph initiatives within organizations, offering a comprehensive framework that blends cutting-edge techniques with real-world case studies. It equips participants with the crucial understanding needed to make informed decisions, optimize initiatives, and unlock the transformative potential of Knowledge Graphs in today’s data-driven landscape.
This half-day workshop looks at the development of data products in detail. It also looks at the strengths and weaknesses of data mesh implementation options for data product development. Which architecture is best to implement this? How do you co-ordinate multiple domain-oriented teams and use common data infrastructure software like Data Fabric to create high-quality, compliant, reusable, data products in a Data Mesh. Is there a methodology for creating data products? Also, how can you use a data marketplace to share and govern the sharing of data products?
In this session Alec Sharp will introduce methods to get people engaged in concept modelling, practice with guidelines to ensure proper naming and definition of entities/concepts/business objects and illustrate the many ways concept models (conceptual data models) support business process change and business analysis.
In this session Mike Ferguson looks at different architectures that recent were offered by many different vendors claiming to be ‘the modern data architecture solution’ for the data-driven enterprise, with support for open table formats such as Apache Iceberg, Apache Hudi and Delta Lake. In addition, we have seen significant new milestones in extending the ISO SQL Standard to support new kinds of analytics in general purpose SQL. He will discuss the impact of this on analytical data platforms and what it means for customers.
In this talk, we will delve deeper into the significance of knowledge graphs as facilitators of large-scale data semantics. The discussion will encompass the core concepts, challenges, and strategic considerations that architects and decision-makers encounter while initiating and implementing knowledge graph projects.
The more regulations that organisations have to deal with (GDPR, Data Act, AI Act) the more important it is to understand your data and data storage. Data modelling is crucial here but which type of data model fits best for which application? Tanja Ubert discusses the most common types of data models, the relationship between them and when best to apply which type.
In this presentation Matthijs Stel will show how data management is implemented in a practical way at Evides – a drinking water supplier for 2.5 million consumers and companies in the South-West of the Netherlands. Where to start? How to engage stakeholders? How to stay relevant? And how to anchor the strategy within the organization?