A Survey of Bigdata Analysis, Extracting Data and Mapping the Data

Abstract

Data mapping is one of the simplest terms is to map source data fields and their related target data fields. Mapping can have a varying degree of complexity, depending on the number, data types, schema, primary keys, and foreign keys of the data sources. Nowadays, Archaeological research is based on an interdisciplinary approach which makes use of a wide range of technologies allowing for the collection of data and information about sites and archaeological findings. The purpose of archaeology is to learn more about past societies and the development of the human race. An essential part of the archaeological data is related to spatial information that links historical contents to the metric reconstruction of monuments and artifacts, and show their mutual relations in a map. A critical a part of the archaeological records is associated with spatial data that links ancient contents to the metric reconstruction. By processing a steady stream of all real-time data, organizations can make time-sensitive decisions faster than ever before, monitor emerging trends, course-correct rapidly and jump on new business opportunities. To design a data mapping framework process, the data from various sources uses a new proposed technique. To secure the high profile raw and analyzed data using the combination of hardware and software any key generation for data extraction and mapping. The information can be accessed only through the authenticated source of the framework and hence duplication and data theft is extremely difficult. This paper follows the various data mapping techniques handled in previous work and also shows the limitations of existing techniques.