Migrating Data Semantic from Relational Database System To NOSQL Systems to Improve Data Quality for Big Data Analytics System

Today, in the computer science world, data has become an essential hub for information processing in general. These data continue to progress in a progressive and exponential way, especially in storage and its technologies. The term big data as we use it for mass volumes of data, offers important techniques for processing, analyzing, and proposing useful information for decision making. NOSQL databases become a modern and indispensable technology to use, to provide scalability to support large data. This is why there is always this challenge for organizations to transform their existing databases to NOSQL databases by considering the heterogeneity and complexity of relational data. In this paper, we propose an approach for the migration of a relational database to another NOSQL. This method has two phases, the first is to transform the relational database to a NOSQL database, and the second is to enhance and improve the quality of the data with cleanup processes to provide and prepare them for big data analytics systems.