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Top1. Introduction
Enterprise organizations nowadays have major problems in handling their big data and how to get the most benefits out of it (Patel, 2015). Many organizations have many systems that can provide data daily. They have many concerns on how they can create and capture new values from their different data sources and how they can integrate different data sources in one data warehouse to facilitate the data analysis process (Agrawal, et al. 1993).
Organizations need to make the data analysis process to create new values and new knowledge from the huge gathered data (Al Omari, et al. 2019). New knowledge creation will be the most important feature that decision-makers need to know, according to marketing challenges and organization strategy (Hussein, et al. 2019).
Managing big data with different data formats and data volumes are the main basis for competition between different companies. When data defined by a numerical representation of some measurement, which now is easy by using available technology that extracts data, analyzes, and convert it into information and finally into new values or knowledge (Muliawaty, et al. 2019).
There is a need to create new values from big data to support decision-makers in taking the correct decisions. The new values can be created using mining association rules (Sony & Baporikar, 2019). Association rules were used to discover the important associations among items in a given dataset based on support value and confidence value (Walaa, et al. 2014). The underlying idea is to identify rules that will predict the occurrence of one or more items based on the occurrences of other items in the dataset (Kielbasa, 2007).
The purpose of big data management system is value creation or value addition for all of its customers and decision-makers (Karimi-Majd, et al. 2015). The core elements of any big data management platform that can be proposed; are to handle these data and extract the new values in new ways as compared to the traditional relational database (Shamim, et al. 2019).
The organizations can define value creation as an action that can be made anytime where the advantages of this action exceed the prices (Chandy, et al. 2017). They can also be defined as new information that leads to preventing an action where the prices exceed the advantages (Pigni, et al. 2016). The new value is created when an incremental opportunity appears, improves upon something that already exists, or reconfigures an existing system or technology to serve some other purposes (Eaton, et al. 2016).
There are different researches presented different approaches to create new values from big data, some of these approaches did not take care of different data operations that needed to be done over the collected data. Some of these approaches did not apply the integration layer and divide the work into blocks or layers. Some of these approaches did not mention the tools and techniques used in the new value creation process. All these researches didn’t introduce a complete approach for organizations to handle all big data activities.