Digital transformation and the data-driven organization are popular topics in boardrooms today because organizations understand the need to do more with data. They want to apply the strengths and benefits of data science, self-service BI, embedded BI, edge analytics, and customer-driven BI. The consequence is that data needs to be deployed more widely, more efficiently, and more effectively. Unfortunately, current IT systems—such as the data warehouse and transactional systems, as well as the new data lake—can no longer cope with the ever-increasing workload. They have already been overstretched. For many organizations, it’s time for new data architectures.
This session discusses two new, future-proof data architectures: the logical data warehouse and the logical data lake architecture. With these, new data sources can be hooked up more quickly, self-service BI can be supported correctly, operational BI and data science can be implemented more easily, and the adoption of new technology is much easier.
The technology to create a logical data warehouse is available: data virtualization. Migration to a logical data architecture is based on a step-by-step process and not a full rip-and-replace approach.