Date of Publication :23rd January 2023

Abstract: The advancement of technology has resulted in prompt action in identifying the various methods of collecting the data generated for later extraction. In the ETL and ELT world, data extraction, commonly known as data mining and AI, helps companies decide as they learn and predict customer behaviors and economic patterns. The onset of technology has highlighted the various data models through which the organization information flow within an organization is hence deciding the data processing and extraction processes such as network, hierarchy, E-R, and the relational model. Data mining occurs through a series of steps to guarantee the generation of valuable data, as exemplified by data cleaning, integration, reduction, transformation, mining, evaluation, and representation. However, data extraction faces various challenges: privacy and confidentiality, data collection, and preparation. This paper highlights the process, and best practices for data modeling as business needs change.

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