A data warehouse is defined as a central repository that allows enterprises to store and consolidate business data extracted from multiple source systems for the task of historical and trend ...

Although difficult, flawless data warehouse design is a must for a successful BI system. Avoid these six mistakes to make your data warehouse perfect.

As companies implement identity resolution solutions, many are left with the challenge of needing to merge offline customer ...

Data lakes and data warehouses are achieving a measure of success in modern data architectures, but the emergence of the data lakehouse offers new challenges and opportunities for database ...

Data analytics have either been centralized or decentralized. Data mesh tried to fix that. The hub-and-spoke model goes further.

One of the most important shifts in data warehousing in recent times has been the emergence of the cloud data warehouse. Previously, setting up a data warehouse required a huge investment in IT ...

Data modeling is the framework that lets data analysis use data for decision-making. A combined approach is needed to maximize data insights.

Oracle Data Warehouse and Amazon Redshift are two popular data warehousing solutions, but which one has your organization's ideal features and capabilities? Read this comparison to find out.