AI and multimodal data are reshaping analytics. Success requires architectural flexibility: matching tools to tasks in a ...

Most modern data architecture layers utilize all or some of the following components: Data sources are fundamental to any data architecture. Sources can be anything from relational databases such as ...

I use the term “universal semantic layer” to describe a thin, logical layer sitting between the data platform and analysis and output services that abstract the complexity of raw data assets ...

This approach works well for smaller companies, but it created problems for larger enterprises that used two or more BI and analytic tools. Now the enterprise is faced with the task of hardwiring two ...

Staging layer: Since not all information might be available to load into the data warehouse server at once, organizations might set up a staging layer as a temporary data landing zone post ETL.

AI fabric architecture is modular, scalable, and future-proof and the key to organizational excellence in the modern business landscape Time flies in the world of data analytics and artificial ...

First, there was a data warehouse – an information storage architecture that allowed structured data to be archived for specific business intelligence purposes and reporting. The concept of the ...

2. More businesses will operationalize AI. Most organizations struggle to analyze the ocean of data they collect. This is because nearly 90% of data is unstructured or has no defined schema.. AI ...