Methods for high-quality statistical data analysis: An objective review

Abstract

This research explores "Big Data" as a pivotal asset in the digital economy, focusing on the computational and statistical challenges posed by its volume, velocity, and variety. The study analyzes contemporary algorithms, highlighting the necessity of transitioning from traditional statistical methods due to their declining explanatory power and computational inefficiency when facing high complexity. The findings emphasize critical issues such as data heterogeneity, noise accumulation, and spurious correlations. The paper concludes that ensuring "Data Veracity" is the primary challenge; without specialized statistical expertise, the risks of inaccurate inference can transform data from a valuable resource into a significant institutional  liability.