THE EFFECTIVENESS OF DATA SCIENCE TECHNOLOGIES IN ANALYZING LARGE-SCALE DATA AND THEIR IMPORTANCE IN OPTIMIZING BUSINESS PROCESSES

The rapid growth of digital technologies has led to an unprecedented increase in the volume of data generated by organizations, governments, and individuals. In this context, Data Science technologies have become one of the most effective tools for analyzing large-scale data and optimizing business processes. This article examines the effectiveness of Data Science technologies in big data analytics and their role in improving operational efficiency, decision-making accuracy, and competitive advantage in business environments. The study is based on factual scientific sources and practical examples from global companies that implement machine learning, predictive analytics, artificial intelligence, and data mining technologies. The research analyzes the methodological approaches used in Data Science and evaluates their impact on operational automation, customer behavior analysis, supply chain management, and financial forecasting. The article concludes that Data Science technologies significantly enhance organizational productivity, reduce operational costs, and improve strategic planning in modern enterprises.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-23
DOI
https://doi.org/10.5281/zenodo.20353247
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

THE EFFECTIVENESS OF DATA SCIENCE TECHNOLOGIES IN ANALYZING LARGE-SCALE DATA AND THEIR IMPORTANCE IN OPTIMIZING BUSINESS PROCESSES

Vosid Vaxob ugli Qarshiboyev
Zenodo (CERN European Organization for Nuclear Research)
Big Data and Business Intelligence
article

THE EFFECTIVENESS OF DATA SCIENCE TECHNOLOGIES IN ANALYZING LARGE-SCALE DATA AND THEIR IMPORTANCE IN OPTIMIZING BUSINESS PROCESSES

Vosid Vaxob ugli Qarshiboyev
article en

Abstract

The rapid growth of digital technologies has led to an unprecedented increase in the volume of data generated by organizations, governments, and individuals. In this context, Data Science technologies have become one of the most effective tools for analyzing large-scale data and optimizing business processes. This article examines the effectiveness of Data Science technologies in big data analytics and their role in improving operational efficiency, decision-making accuracy, and competitive advantage in business environments. The study is based on factual scientific sources and practical examples from global companies that implement machine learning, predictive analytics, artificial intelligence, and data mining technologies. The research analyzes the methodological approaches used in Data Science and evaluates their impact on operational automation, customer behavior analysis, supply chain management, and financial forecasting. The article concludes that Data Science technologies significantly enhance organizational productivity, reduce operational costs, and improve strategic planning in modern enterprises.

Zenodo (CERN European Organization for Nuclear Research)
Tashkent State University of Economics (UZ)
Openalex Percentile: Top 3%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.