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. At the same time, they must manage complex and often costly infrastructure landscapes. These issues hinder companies from effectively leveraging their data for business purposes.
Drawing from real-world experience, this presentation will explore how we address these challenges by building reliable and scalable data platforms with reasonable costs. It will also cover solutions to help operational teams provide their data and to observe the flow towards analytics systems. In addition to discussing architectures and design considerations the presentation will also highlight tools and techniques used to implement these platforms.
Speaker
Matthias Niehoff
Head of Data and Data Architecture @codecentric AG
Matthias Niehoff works as Head of Data and Data Architect for codecentric AG and supports customers in the design and implementation of data architectures. His focus is on the necessary infrastructure and organization to help data and ML projects succeed.
