The difference depends on how you define "mathematical analytics".

One, for example finds this:

" We find patterns and derive insights by visually exploring data. Predictive and prescriptive analytics supports better decisions and smarter data based-actions. Including big data-enabled algorithms. " (https://enyanalytics.com/drill_service/mathematical-analytics/)

So it seems that mathematical analysis is a subset of mathematical analytics.

Wow. It is beautiful.

Mathematical analysis is the branch of mathematics dealing with limits and related theories, such as differentiation, integration, measure, infinite series, and analytic functions.[1][2]

These theories are usually studied in the context of real and complex numbers and functions. Analysis evolved from calculus, which involves the elementary concepts and techniques of analysis. Analysis may be distinguished from geometry; however, it can be applied to any space of mathematical objects that has a definition of nearness (a topological space) or specific distances between objects (a metric space).

See https://en.wikipedia.org/wiki/Mathematical_analysis

The Mathematical Analytics (and Operations Research)

major provides training for students planning careers in any field that requires mathematical methods. For example: the discovery of meaningful patterns in high-dimensional data; scientific approach for making decisions based on models that optimize the decision parameters such as cost, time-to-completion, transportation logistics, scheduling of tasks, etc.; data visualization to communicate and present decisions to others. Graduates of our program will distinguish themselves for their problem-solving skills, computational and modeling ability, and excellent communication skills. These abilities allow them to pursue scientific or technical careers in industry, education, or government. In addition, their strong analytic skills prepare them well to continue with graduate education or to participate in research and development, and other creative and innovative efforts in science, arts and humanities, engineering, and business.

See https://www.ucdavis.edu/majors/mathematical-analytics-and-operations-research/

The above describes analytics, in contrast to mathematical optimization - they are quite distant from each other, I should say, as mathematical optimization has a much stronger mathematical focus. Yes, analytics is part of operations research, indeed. If I were to look at my bookshelf - 2000 books or more - then there are no analytics books at all, but plenty of operations research and mathematical optimization ones, among, of course, my pure math books. You may think that the themes are close to each other, but they are not.

Dear Tamas,

thank you for your comment. I used your reference when I wrote the related paper. Your comments " So it seems that mathematical analysis is a subset of mathematical analytics ". If you use the classical definition, mentioned by Maged, you cannot get the result "mathematical analysis is a subset of mathematical analytics", although I am also trying to use it as my idea development.

Dear Michael,

thank you for your comment. However, based on my research, analytics was introduced in 1936. It has been a topic since then in particular in business. Recent analytics is hot because of big data. Big data analytics is hotter. For detail, see my recent book: Sun Z (2019) Managerial Perspectives on Intelligent Big Data Analytics. IGI-Global, USA. My new idea is that we have only one mathematical analytics, although we have the web of x analytics in practice.

This is the reason why I ask the question: what is mathematical analytics, and

How can we differentiate mathematical analytics from mathematical analysis?

I will release my research results soon.

Prof. Zhaohao Sun

2019-8-8