The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

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 ...

Choosing between your data warehouse and a packaged CDP depends on control, speed and operational complexity. The post Warehouse-native CDPs vs standalone platforms explained appeared first on MarTech ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

As more organizations embrace big data and analytics to gain insight from extremely large datasets, the tools and systems used to manage data have grown, changed, and mul­tiplied. Instead of just ...

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 ...

Most projects benefit from having a data model. This article gives an overview of the most common types. At its heart, data modeling is about understanding how data flows through a system. Just as a ...