Data Architectures in the Real World

The right data architecture and platform for data analysis and AI is different for every company. What different approaches are there? Which constraints influence the approach and the final solution? Does everyone want the one, magical platform or are there also very tailored, specific solutions? The challenges also differ: some lack know-how and capacity, others are overwhelmed by the complexity of their own IT landscape, others have to set up everything without the help of managed services.

With a high degree of practical relevance, I report on different projects and situations – and show a wide range of modern data projects and approaches.

Prior knowledge:
Experience with data architectures, platforms and infrastructure is helpful

Learning objectives:
– Overview of the possible solutions for modern data architecture
– Understanding which constraints influence the architecture and in what way
– Overview of decisions that are made when designing architectures, including the trade-offs that are usually taken into account.
– Application of the different perspectives in your own environment