If you’re on the fence about modernizing your data warehouse, consider this: Data warehouse technology hasn’t changed much in almost 40 years, the equivalent of eons in the fast-paced technology sector. During that time, it’s performed admirably as the centralized repository for enterprise-wide analytics, capable of storing and processing comparatively large and homogenous data sets. Support for strong-typing, enforced constraints, and CRUD (Create, Read, Update, Delete) operations was essential for its wide adoption and ultimate success. But in recent years, the advent of ‘Big Data,’ and a voracious appetite for data in general, has exposed some technological gaps that legacy warehouses just aren’t equipped to handle.
