Design a New Learning based Method for Smart Semantic Data Management System

Now a days, enormous quantity of data is being generated everyday from various sources such as online data, social media, scientific data, text data, images etc. When data becomes large in Volume, generated in high Velocity and Variety of data in the form of structured data or unstructured data is known as Big data. Traditional database tool such as RDBMs cannot deal with Big data. Challenges in big data are information storage, search and retrieval of data. Since most of the data are in different formats, we need tools and technology for transforming, analyzing, visualising data and extracting information for decision making. Collection of large data set is a significant issue and to make sense from that big data is a problem. We need ways to find semantic information from the data to help users make better decisions making. To facilitate better data management, Semantics can be used. Semantic can be efficiently use for management of large data sets and better information retrieval process. Semantic annotation of heterogeneous data sets could facilitate the search and retrieval using the concepts contained in them. This paper proposes a new methodology for designing a Learning based Method for Smart Semantic Data Management System.