Big Data Integration Solutions in Organizations: A Domain-Specific Analysis

Abstract

Big Data Integration (BDI) process integrates the big data arising from many diverse data sources, data formats presents a unified, valuable, customized, holistic view of data. BDI process is essential to build confidence, facilitate high-quality insights and trends for intelligent decision making in organizations. Integration of big data is a very complex process with many challenges. The data sources for BDI are traditional data warehouses, social networks, Internet of Things (IoT) and online transactions. BDI solutions are deployed on Master Data Management (MDM) systems to support collecting, aggregating and delivering reliable information across the organization. This chapter has conducted an exhaustive review of BDI literature and classified BDI applications based on their domain. The methods, applications, advantages and disadvantage of the research in each paper are tabulated. Taxonomy of concepts, table of acronyms and the organization of the chapter are presented. The number of papers reviewed industry-wise is depicted as a pie chart. A comparative analysis of curated survey papers with specific parameters to discover the research gaps were also tabulated. The research issues, implementation challenges and future trends are highlighted. A case study of BDI solutions implemented in various organizations was also discussed. This chapter concludes with a holistic view of BDI concepts and solutions implemented in organizations.

A Framework for Integrating Green Highway Performance Data with the Carbon Footprint Calculator in Malaysia

“…Another benefit of database integration and consistency is the use of widely agreed data descriptions and standardized system-wide formats. Regardless of the integration approach implemented, a common data dictionary or global standard for data interpretation, representation, distribution, and communication may be essential for data integration (Karanam, et al, 2021). Nonetheless, concessionaires have found several problems in creating and applying data standards and adapting existing legacy data to these new standards.…”