Description: Logical Data Analysis is a fundamental process in the field of databases and Big Data, focusing on examining the logical structure of data and the relationships that exist between them. This analysis allows information professionals to understand how data is organized, facilitating the identification of patterns, trends, and correlations. Through techniques such as normalization, the aim is to optimize the structure of databases, eliminating redundancies and ensuring data integrity. Furthermore, Logical Data Analysis is crucial for designing database schemas, where entities, attributes, and relationships are defined, which in turn influences the efficiency of queries and the overall performance of the system. In a world where the amount of data generated is overwhelming, this analysis becomes an essential tool for informed decision-making and the creation of predictive models. Its relevance extends across various industries, from healthcare to commerce, where the ability to interpret data logically can make a difference in business strategy and technological innovation.
