Data lifecycles analysis: Towards intelligent cycle

As companies generate and handle increasingly large amounts of data along with the Big Data era, several model of data lifecycle have been proposed to deal with this situation. The analysis, the management and the use of data becomes more complicated or almost impossible in some cases for the companies. To transform these data to a knowledge, the choice of the adequate lifecycle that matches with the company expectations becomes essential. For this goal, this paper aims to be a guide to assist companies to choose a lifecycle that fits their data management vision. For this, we identify the relevant criteria of selection cycles and defined a rating system to each of these criteria. In this paper, we study the available lifecycles of data in the literature that we consider relevant. As a result of this study, we classify these cycles following two types: first analysis oriented phases and the second based on relevant criteria.

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