Big Data Financial Analysis of BYD Company Profitability Based on Power BI Software

Tieping Wang

2022

Abstract

Big data financial analysis comprehensively considers all the information of the company and can comprehensively reflect the financial status of the company. This paper uses Power BI software to present the results of big data financial analysis on BYD's profitability; using industry analysis and trend analysis, it analyzes BYD's profitability from three aspects: capital profitability, asset profitability and commodity profitability. The industry analysis method can be used to observe the current level of BYD in the industry, compare the company's five-year average, judge the company's development status, and study the strengths and weaknesses of the target company's capabilities; the trend diagram method can be used to observe BYD in different time periods. Changes in indicators, find out the hidden problems in the company's operation process, analyze the reasons for changes and put forward optimization suggestions.

Paper Citation

in Harvard Style

Wang T. (2022). Big Data Financial Analysis of BYD Company Profitability Based on Power BI Software. In Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME; ISBN 978-989-758-636-1, SciTePress, pages 49-54. DOI: 10.5220/0012023300003620

in Bibtex Style

@conference{icemme22,
author={Tieping Wang},
title={Big Data Financial Analysis of BYD Company Profitability Based on Power BI Software},
booktitle={Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME},
year={2022},
pages={49-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012023300003620},
isbn={978-989-758-636-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME
TI - Big Data Financial Analysis of BYD Company Profitability Based on Power BI Software
SN - 978-989-758-636-1
AU - Wang T.
PY - 2022
SP - 49
EP - 54
DO - 10.5220/0012023300003620
PB - SciTePress