Data mining to optimize the organization
Nowadays, the utilization of data for a specific purpose has been exponentially increased, as known that there is an enormous database (big data), which has been typically composed a mixture of either necessary data or unnecessary data that poses a difficulty to utilize only the specific data for an organization’s specific purposes. The selection of necessary data from big data aims to increase the performance and the competitiveness of organizations. However, as mentioned the mixture of necessary and unnecessary data make the difficulty to classify and individualize data separately. A data science therefore, plays an important role to establish either tools or methods that would facilitate the separation of a mixture of data by a combination of statistic, mathematics and computer science together. Extraction method of necessary data is one of foundational methodology of data science, which will help to acquire only necessary data from a big data for a specific purpose. This is used to extract and analyze the factors that affect the organization performances for instance, the effect on business-marketing and the organization benefits. This review article has an objective to describe and overview an overall of an extraction method of necessary data in order to maximize the utilization of necessary data.