Researchers have developed a conceptual and logical modeling methodology that treats measures, granularity hierarchies, and ...

Storage options abound when it comes to processing, managing and deriving the most value from floods of structured and unstructured data -- among them, data warehouses, marts and lakes. Each of these ...

reality-testing data warehousing and business intelligence (BI) projects. marts can be built from the available source data. . Analyzing a new or updated source system against an in-place data ...

I talk to a lot of different businesses about their data, and, without fail, some form of the same question always comes up: “What is the most common reason you see data warehouse projects failing?” ...

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 ...

Now that data warehousing has become ubiquitous in the corporate world, "clean slate" designs of entirely new decision support systems are becoming somewhat rare. Instead, designs and roadmaps are ...

For decades, the enterprise data warehouse (EDW) has been the aspirational analytic system for just about every organization. It has taken many forms throughout the ...

Data warehouses and data lakes both offer more flexible, scalable, and agile methods for storing data from multiple sources and in various structures. Unlike traditional databases, these advanced ...

Looking for enterprise data warehouse development in 2026? We reviewed the top companies for scalability, security, cloud ...

Demand for data warehousing (DW) technologies held steady in 2010 even as many other IT categories retrenched in a tough economy. That's the macro take detailed in Gartner's just-released "Magic ...

The "data" part of the terms "data lake," "data warehouse," and "database" is easy enough to understand. Data are everywhere, and the bits need to be kept somewhere. But should they be stored in a ...