However, that doesn't mean that you should forget about Data Mining and divert your entire analytics budget to Predictive Analytics. I'll explain why in another blog post in future.

Before marketers commit to and execute their AI strategy, they need to understand the opportunity and difference between data analytics, predictive analytics and AI machine learning.

What is the difference between data mining and data science? Data mining is a critical component of data science, a broader field encompassing various techniques and practices for analyzing and ...

Deriving inferential statistics from recurrence plots: A recurrence-based test of differences between sample distributions and its comparison to the two-sample Kolmogorov-Smirnov test.

However, there are some fundamental differences between these concepts in scope and function. BI is an overarching framework for analytics and AI.

There are many similarities between data migration and data integration, but they also have some key differences. Learn what they are.

Data analytics is the science of analyzing raw data in order to make conclusions about that information. It helps businesses perform more efficiently and maximize profit.