Data cleaning in financial analysis

Authors

DOI:

https://doi.org/10.5377/reice.v1i2.18869

Keywords:

Analysis tools, Data Cleaning Methods and Techniques, Financial Analysis

Abstract

Cleaning databases was crucial for effective financial analysis, improving data quality, reducing errors and optimizing resources. This process included identifying and removing irrelevant and duplicate data, as well as correcting errors and inconsistent data. Database management tools, data duplicators and validators were used, respecting the privacy and protection of personal data according to applicable regulations. The results showed that database cleaning is essential for the integrity and quality of data in financial analysis, fundamental for business sustainability. Upon completion, comfort with the analysis and information obtained was improved, increasing efficiency and productivity in financial analysis. Much data was found to be unstructured, making it difficult to optimize processing. Continuous data generation complicated collection and management. The analysis allowed us to decompose and synthesize the definition of data cleaning, methods and techniques for its execution, and processing mechanisms. Various tools were also presented to manage information, providing ideas to innovate, grow in the long term and create more effective strategies, improving efficiency and productivity in financial analysis.

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Published

2024-10-04

How to Cite

Cruz Orozco, O. J. (2024). Data cleaning in financial analysis. Revista Electrónica De Investigación En Ciencias Económicas, 100–130. https://doi.org/10.5377/reice.v1i2.18869

Issue

Edición Especial: IIS Septiembre (2024)

Section

Research Articles

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