Category: Data Warehousing

Kimball-style dimensional modeling has been the go-to architecture for most data warehouse developers over the past couple of decades. The denormalized nature of these schemas, coupled with optimization for history maintenance, makes the dimensional model an ideal tool for the…

Data warehouses have long served as a single source of truth for data-driven companies. But as data complexity and volumes increase, it’s time to look beyond the traditional data ecosystems. In today’s digitized era, organizations must adapt to the evolving…

Most enterprises out there rely on a data warehouse as a single source of truth — a consolidated data repository that serves as a reporting layer for companies to identify trends and gain valuable business insights. However, to maximize performance…

There are two types of decision-makers: those who make decisions based on assumptions and those who take actions based on facts. From a logical and statistical perspective, the latter category makes better choices that help their organizations develop and grow….

In 1996, Ralph Kimball introduced the world to dimensional modeling for building data warehouses. Designed to optimize databases for storage and faster data retrieval, the bottom-up approach became quite popular. Thus, organizations increasingly started using a dimensional data model to…