NODW Framework for Data Warehousing -A NoSQL Big Data Perspective

The idea of data warehousing is data model independence and does not require the adoption of any data model. Nevertheless, relational databases are assumed to be used in the common notion of data warehouses. Typically, it is thought that data warehouses are relational data storage, and relational database management systems (RDBMSs) are used to process them. Data warehousing frequently features Structured Query Language (SQL) reporting capabilities, enabling access to the data in a standard manner. "Not only SQL" (NoSQL) databases are viewed as high-speed data structures appropriate for filtering and lookup operations suitable for complex processing tasks. Traditional database systems are incapable of dealing with vast volumes of data for knowledge discovery and complex analytics. This incapability is facing a paradigm shift in technologies, techniques, concepts, and methods. The key problem is to achieve a good balance between the characteristics of classical data warehouses employing relational database management systems and the potential afforded by NoSQL database management systems in a big data environment. This paper covers the integration of disparate big data technologies using an opensource NoSQL columnar database management system to address the possibility of constructing data warehouse (DW) solutions in a big data environment.