Data Transformation from SQL to NoSQL MongoDB Based on R Programming Language

Owing to their high availability and scalability, NoSQL databases are becoming more popular for Big data applications in web analytics and supporting large websites. Moreover, each NoSQL system has its API which does not support industry standards like SQL and JDBC, integrating these systems with ot...

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Bibliographic Details
Published in:2021 5th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) pp. 399 - 403
Main Authors: Hasan, Forat Falih, Bakar, Muhamad Shahbani Abu
Format: Conference Proceeding
Language:English
Published: IEEE 21.10.2021
Subjects:
Big Data
Computer languages
Data analysis
Data integrity
Data Transformation
ETL
NoSQL
NoSQL databases
SABR Algorithm
Scalability
Structured Query Language
Transforms
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Summary:Owing to their high availability and scalability, NoSQL databases are becoming more popular for Big data applications in web analytics and supporting large websites. Moreover, each NoSQL system has its API which does not support industry standards like SQL and JDBC, integrating these systems with other enterprise and reporting software takes more time. The main requirements of Big data and data analytics are transforming the data from SQL databases to NoSQL data structures to represent the data. In this work, we presented a method to transform the data from different types of SQL databases to the desired NoSQL database based on the R programming language. The proposed work is based on the R environment used to handle the data from the source system to the target databases and meet the data quality requirements in data transformation. The results confirmed that the development provided a good solution for the data transformation from SQL to NoSQL by taking into account the data quality requirements.
DOI:10.1109/ISMSIT52890.2021.9604548