Abstract: Our civilization has become much more computerised, which has greatly improved our ability to generate and gather data from a variety of sources. Almost every element of our lives has been inundated with an enormous amount of data. It is necessary to convert the enormous volume of data into knowledge and relevant information. Data mining is a promising and flourishing field of computer science as a result of this. Data mining is the automated or practical extraction of patterns that represent implicitly stored or recorded knowledge from huge information repositories, such as databases, data warehouses, the web, and other big information repositories or data streams. Any type of data can be used for data mining as long as it has value for the intended application. In this paper, we discuss in detail data warehouse and data warehouse data, which is almost basic form of data for data science applications. We also present to you a typical framework of a data warehouse and data pre-processing techniques. Additionally, we talk about OLAP (Online Analytical Processing) Data Marts, a subset of an organisational data store that is typically focused on a single objective or key data area and can be disseminated to meet business requirements.
Keywords: computerization, data science, databases, data warehouses, data pre-processing techniques, OLAP (Online Analytical Processing) Data Marts, Total Quality Management.
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DOI:
10.17148/IJARCCE.2023.12136
