Inmon versus Kimball is one of the biggest data modelling debates among data warehouse architects. Here is some help to select your own approach.

In data warehousing, the logical model is often an afterthought or merely a carbon copy of the physical sans platform-specific properties. That limits the visibility and the use of the model to a ...

Designing your data warehouse Let’s start at the design phase. When planning your design, the vision for your new data warehouse is best laid out over an enterprise data model (EDM), which consists of ...

One day, corporations awoke to the fact that having data was not the same thing as having believable data. They awoke to discover the meaning of 'data integrity.' That was the day the enterprise data ...

Cloud-native Snowflake seeks to overcome the challenges of previous generations of data warehouse technology and embrace big data. How is its approach unique?

Data warehouse designs are the foundation of business intelligence projects. Find out 5 mistakes you need to avoid now.

How does a data warehouse work? A data warehouse is a system that stores and analyzes data from multiple sources. It helps organizations make better decisions by providing a centralized view of their ...

A quick quide to shifting from data warehouse, data lake or legacy systems to a data lakehouse without disrupting business applications.

The company had used a central data warehouse for data analysis since its early days, but scalability eventually became a problem.

Software giant SAP Wednesday unveiled SAP Datasphere, the next generation of the company’s cloud data warehouse service with new data cataloging, simplified data replication and enhanced data ...