Data science teams capture, store, and analyze data to extract valuable information and insight. In recent posts, I focused on capturing and storing three types of data — structured, semi-structured, and unstructured — and I encouraged readers to avoid the common trap of allowing big data to become big garbage. In this article, I shift […]
The key difference between a data warehouse and a data lake is how the database is structured and how it's used.
Machine learning is one of the best ways to gain insights from your big data. See how you should approach this data science challenge.
Examples of machine learning applications that are designed to solve complex business challenges.
A database schema is the organization of data in a database. They are usually found in a relational database management system.
With machine learning you have to create a culture that can ask data science questions.
