Forth, the high-throughput data exhibit a large variability and redundancy, which make the mining of useful knowledge difficult.
Particularly, data mining can extract useful knowledge from the collected data and provide useful information for making decisions [1, 2].
Due to the increasing occurrence of very large databases, mining useful information and knowledge from transactions is evolving into an important research area.
"We are traveling, getting much more informed, and the information gives us useful knowledge," he said.
The analysis has consisted on the application of different data mining techniques to extract useful knowledge, traffic forecasting methods to perform accurate predictions, and statistical analyses to model and validate the system reliability (comparing to other real data sources).
In their review, Tsai et al. [61] discuss big data analytics and related open issues, focusing on how to develop a high performance data processing platforms to efficiently analyze big data and to design an appropriate mining algorithm to extract useful knowledge from big data, in addition to presenting some research directions.
During data mining process, we can achieve useful knowledge and hidden patterns within the data and consequently we will discover the meaningful knowledge.
In this paper, we adapt and extend association rule mining and clustering algorithms to extract useful knowledge regarding diabetes and high blood pressure from the 1999 2008 survey results, thus demonstrating how data mining techniques may be used to support evidence-based medicine.
Data mining techniques have been designed to discover useful knowledge from database [1, 2], in fact, data mining techniques play a vital role in many business analytics and predictive applications that come to complete data analysis and predictive techniques.
Consequently, data mining techniques capable of automatically extracting useful knowledge to provide clinical decision support may be applied.
