Research Challenges for Dataspace System and Big Data Using Artificial Intelligence

Abstract

Dataspace has recently gained much attention in machine learning. Managing the heterogeneous data at the different levels in the organization very tedious task, data in the organization are storing in different formats due to various formats. In these organizations these data may of following types, Structured, data in unstructured formats or semi-structured. In the underlined approaches in the organizations are unable to handle and map these data for better decisions and unable to retrieve efficient data with accuracy which are also stored in huge volume of data as in big data format. Using the Artificial Intelligence (AI) and Machine learning approaches, we can develop software and tools with extensive feature for the analysis interests. As the latest ICT research are more emphasis of technical and specialized aspects. Using these approaches, big data users can easily automate, predict the results for better analysis. Present approaches are very time consuming, low accurate data due to direct involvement of the humans. By using the AI and Machine learning on Big data, we can predict and analyses the heterogeneous data sets easily and with accuracy. Combining these approaches together can initiates and develop a model that may sole the real-life data with better economic results with enhanced employment for humans. In this paper, we have discussed combined the Big data, Dataspace, Artificial Intelligence and machine learning for with their research challenges.

Keywords: Artificial Intelligence (AI), Big data algorithms, Database ranking, Dataspace, DSMS, Heterogeneous data, Machine learning.

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