In a world powered by data, crafting the right architecture has never been more critical—or more complex. With an ever-growing arsenal of tools and solutions, designing a robust, future-ready data architecture requires not just expertise, but pragmatism and foresight. The challenge? Building scalable systems that meet the demands of today while anticipating the needs of tomorrow—especially when AI and machine learning enter the mix.
As companies embrace Data Mesh architectures to decentralize data ownership, they face a cascade of hurdles: scaling infrastructure, integrating real-time data streams, ensuring data governance, and automating agile data pipelines—all while keeping costs in check. The race to innovate is on, and the winners will be those who can turn these challenges into opportunities.
Join us at our Modern Data Architectures track, where industry experts will share the actionable insights, cutting-edge strategies, and real-world case studies you need to navigate this evolving landscape. Whether you're leading your company's data transformation or fine-tuning your existing architecture, this is your chance to discover the best practices in Modern Data Architecture and becoming best equipped to design a future proof data application.
From this track
Reliable Data Flows and Scalable Platforms: Tackling Key Data Challenges
There are a few common and mostly well-known challenges when architecting for data. For example, many data teams struggle to move data in a stable and reliable way from operational systems to analytics systems.
Matthias Niehoff
Head of Data and Data Architecture @codecentric AG