Sentence examples for data mining and analytical from inspiring English sources

The Resources application provides tutorials, customized reference datasets, and data mining and analytical tools to explore the ImmPort data model and analyze its content.

In this paper, we focus on reviewing the application of data mining and analytical techniques designed so far for (i) prediction, (ii) detection, and (iii) development of appropriate disaster management strategy based on the collected data from disasters.

And to ensure that the company's tools can reach the widest audience, Addepar opened an API and has integrated its data mining and analytical toolkit into products for Salesforce, FolioDynamix, icapital Network, Citco Fund Services , RedBlack Software Blas Portfolio, Quovo and others.

Research throughout all levels of accessible data, using various data mining and analytical techniques, can be used to help the healthcare system make decisions faster, more accurately, and more efficiently, all in a more cost-effective manner than without using such methods.

Because homology is the central concept in evolutionary comparative biology, addressing this challenge with appropriate data mining and analytical tools has to become a priority in the burgeoning field of visual computer analyses.

We use proprietary data-mining and analytical capabilities to help guide consumers through the health maze.

"The state-of-the-art analytical and computational processes" section describes the state-of-the-art analytical and computational processes: data mining and context recognition, and also points out basic issues of context-aware applications.

Analytical CRM frequently uses data mining and pattern recognition to accomplish this task -- it works well for companies in higher priced markets with a lot of competition.

The assumptions we make about this complexity greatly influences the analytical methods we choose for data mining and, in turn, our results and inferences.

The data mining and functional interpretation of datasets to access biologically interpretable results pose many analytical challenges, which have been recently reviewed by Kumar and Mann (2009).

In particular, online analytical processing (OLAP) and decision support systems (DSS) have become popular for data mining and business analysis.