A study of conceptual data modelling in the era of big data: a case of Zambia.

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Kaputula, Listone
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University of Zambia
The way data is collected and stored has evolved over time due to various developments which have led to advancements in database technologies. Few decades ago, only structured data were stored, however, with the increase in the business demand for data in this competitive global market, developments in new technologies for storing data has exponentially emerged. This has resulted in unstructured data also being accommodated in the databases. These new technologies have, however, come with challenges on how unstructured data can be modelled before it is stored. This research project dealt with the study of the conceptual data modelling applied in the era of digital world especially when storing data in NoSQL databases. The researcher, further explores the use of non-relational databases (type of databases which is developed to handle unstructured data) in the selected industries from public, private and non-governmental organisations in Zambia. The study was conducted to have feasible approach for conceptual data modelling that can help to mitigate the challenges of conceptual data modelling for non-relational databases. From the study, indication shows that most research works are on transforming conceptual data models for relational database to a particular logical or physical model of a non-relational database. Further, the study shows that most local organisations use relational databases and have limited or no knowledge on NoSQL databases. The results show lack of skills to create conceptual schema for non-relational database was a hindrance to Big Data implementation. This is attributed to insufficient knowledge about Big Data. The findings in this study reveals that local firms and organisations are yet to start implementing non-relational databases for data storage. It also showed that the use of Big Data is still at infancy stage. The results obtain in this study were used to create a proposed approach for conceptual data modelling that can be used in NoSQL databases. Key words: Big Data, Conceptual data modelling, Database, Dataset, NoSQL
Management information systems. , Data mining. , Information storage and retrieval. , Big Data