Physical: Design a model for implementing the logical model that considers the RDBMS to be used. During this phase, you’ll describe tables, indexes, and so on. The physical model is built on tables.

So in the early phases of a project, you need to get a good sense of the data. “Conduct an exploratory analysis,” said Dan Simion, who is the VP of AI & Analytics at Capgemini North America ...

To gain business value from data, enterprises need to get their data architecture right – and the right business leadership and culture is critical to that.

Confidentiality, to a lesser extent, and integrity, to the greatest extent, are the most important considerations with AI ...

Design thinking is critical for developing data-driven business tools that surpass end-user expectations. Here's how to apply the five stages of design thinking in your data science projects.

Let’s examine how to create a “three-statement projection model” for a company by estimating its cash flow, cash and debt balances over the years.