Challenges with data warehouses
Data warehouses aren’t actually designed for large-scale data analysis, and when used in this way these systems will reach their structural and capacity limits very quickly. We now generate enormous volumes of unstructured data which needs to be processed quickly.
Another limitation is the fact that high-quality analyses now draw on a variety of different data sources in different formats, including social media, weblogs, sensors and mobile technology.
A data warehouse can be very expensive. Large providers such as SAP, Microsoft and Oracle offer various data warehouse models, but you generally need relatively new hardware and people with the expertise to manage the systems.
Data warehouses also suffer from performance weaknesses. Their loading processes are complex and take hours, the implementation of changes is a slow and laborious process, and there are several steps to go through before you can generate even a simple analysis or report.