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 ...

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 ...

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 ...

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 ...

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

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

Learn how one higher education institution is modernizing and strengthening its endowment and fundraising strategy by ...

Part 4 of CRN’s Big Data 100 takes a look at the vendors solution providers should know in the data warehouse and data lake systems space.