The phrase "massive data analysis" is grammatically correct and is commonly used in written English in fields such as data science, computer science, and business.
Example: The company invested in a team of experts to conduct massive data analysis in order to gain insights on customer behavior and improve their marketing strategies.
Her main research interest is theoretical aspects of massive data analysis.
The main problem in the process of massive data analysis over cloud using these techniques is the computational costs associated with image processing tasks.
There's a saying in the sciences, "Statistics means never having to say you are certain". In any massive data analysis, for instance, there will be random correlations that look "significant" but actually are noise, not signal.
5/1/2016 - Read a Q+A with Jasjeet Sekhon, senior fellow at the Berkeley Institute for Data Science, who uses massive data analysis to examine persuasion in elections and the effectiveness of digital advertising and personalized medicine.
This paper builds on a massive data analysis that has been heavily vetted for more than a year, but pushes into new terrain with particularly strong conclusions about the human forces driving warming.
A cascade-style optimizer for Scope, Microsoft's system for massive data analysis, is designed in [33].
The study indicates that massive learning data analysis is the key feature of smart classroom which is distinguished from the traditional computerized classroom.
Developing population scale solutions through massive health data analysis will increasingly be used to drive public health solutions at local, regional and national levels.
To deal with these massive data, elaborated sequence analysis pipelines are employed.
The production control task of scheduling and keeping track of the different orders requires rapid, massive data gathering and analysis.
The Facebook data-gathering feature, called an API, was a common technique at the time for assembling massive data troves for analysis, including names, hometowns, work histories, religious affiliations and personal preferences.
