Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A data warehouse is defined as a central repository that allows ...

Think about the term “data warehouse”: it conjures up images of days long gone by when IT organizations were primarily concerned with packing up all their digital stuff into standard-sized boxes and ...

Many organizations nowadays are struggling with finding the appropriate data stores for their data. Let’s zoom in on some key data structures to facilitate corporate decision making by means of ...

Essentially, a data warehouse is an analytic database, usually relational, that is created from two or more data sources, typically to store historical data, which may have a scale of petabytes. Data ...

Data warehousing solutions enable users to process their organizational data and gain more insights from their data analysis. But with so many different types and vendors of data solutions on the ...

We recently looked at the idea of the data lake, so now it’s time to head downstream and look at data warehouses. We’ll define data warehouses, look at the data types they comprise, the storage they ...

The data lakehouse – it’s not a summer retreat for over-worked database administrators (DBAs) or data scientists, it’s a concept that tries to bridge the gap between the data warehouse and the data ...

Welcome to the new kid on the block, same as the old kid but sharper, tougher and even more relevant to business than before. Who can it be, what do we call her and where does she live? Well here’s a ...

Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping a toe: Integrating a legacy data warehouse into a data lake leverages the structured systems that have been ...