Boston Journal of Computers & Information Technology

Big Data, Data & Databases

Our journal publishes double-blinded, peer reviewed, high-quality research papers on latest and advanced researches of Big Data, Data and Databases.

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Guide To Publish Research
Boston Research Journals


2231-DSDS (Print)
22313-FSWS (Online)

Acceptance to publication

28 days




Creative Commons 2.0 Generic

Computers & Information Technology


The journal of computer science is a well-known journal that primarily focuses on computer science and technology. The journal contains the original and progressive research papers in this discipline in order to provide knowledge. We aim to become a reference research publication. We publish and review original and authentic research papers as well auxiliary materials such as case studies, technical reports, etc. by scholars and researchers all across the world. We welcome submission of papers concerning any branch of computer science and their application in business, industry and other organizations.

Acceptance Rate 31%
Quantopian Grade 84.4%
  • Well-established international journal of scientific research involved in all aspects of computer science and technology.
  • Publish new and refined research and selected scientific journals articles/research papers from all over the world.
  • Promote insight and understanding of the latest trends in computer science and technology.

BRJCIT: Big Data, Data & Databases


The objective of our journal is to produce peer-reviewed, authenticated research papers on various theoretical as well as applied disciplines of Big Data, Data, and Databases prepared by scholars and researchers all across the world. Our journal does not just concern the field of Big Data, Data, and Databases but also includes all the scopes that are mildly or completely related to these fields providing our authors a single platform for all their works.

  • DBMS
  • Database processors & their security
  • Data collection and protection
  • Data analysis
  • Database management systems
  • SQL for data science
  • Data Warehousing for Business Intelligence
  • Relational database systems
  • Cloud Engineering with Google Cloud
  • Using Databases with Python
  • Network Security & Database Vulnerabilities
  • Data Warehousing for Business Intelligence
  • Oracle SQL
  • Database Theory
  • Database Administration
  • Systems Analysis
  • Web Application Database Development
  • Computer Networking, Backup, and Recovery
  • Unix Operating System
  • Database design
  • ETL testing
  • Microsoft SQL Server database
  • Data Management and Analytics
  • Performing Data Definition and Manipulation in SQL
  • Databases: Relational Databases and SQL
  • Data Storage and Processing
  • Enterprise Data Management
  • Fundamentals of database systems
  • Core Database Concepts

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