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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62083
Volume:
10 |
4 |
April 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Information Technology
MES’s D.G..Ruparel College of Arts Science and Commerce.
Information Technology
MES’s D.G..Ruparel College of Arts Science and Commerce.
Information Technology
MES’s D.G..Ruparel College of Arts Science and Commerce.
Information Technology
MES’s D.G..Ruparel College of Arts Science and Commerce.
Sales data analysis plays a crucial role in understanding business performance and making informed decisions. With the increasing availability of data, tools like Power BI enable efficient data visualization and analysis. This research paper focuses on analyzing sales data using Power BI to identify trends, patterns, and key performance indicators (KPIs). The study demonstrates how interactive dashboards improve decision-making, enhance business insights, and increase overall efficiency. However, challenges such as data quality issues and technical expertise requirements remain. Furthermore, this study highlights the importance of real-time data monitoring and its impact on strategic planning. It also explores how visualization techniques such as charts, graphs, and filters simplify complex datasets. The research emphasizes the role of data-driven culture in modern organizations. Additionally, it showcases how businesses can identify high-performing products and regions through effective analysis. The findings suggest that integrating BI tools into business processes leads to better forecasting and improved operational efficiency.
KEYWORDS
Sales data analysis using Power BI provides valuable insights that help organizations make better decisions. Visualization simplifies complex data and improves understanding. While challenges exist, the benefits of using Power BI in sales analysis are significant for business growth.
APA Style· Chen, H., Chiang, R., & Storey, V. (2012). Business Intelligence and Analytics · Few, S. (2013). Data Visualization Principles · Sharda, R., Delen, D., & Turban, E. (2020). Business Intelligence IEEE Style1. H. Chen et al., "Business Intelligence," 2012 2. S. Few, "Data Visualization," 2013 3. R. Sharda et al., "Business Intelligence Systems," 2020
Publication Date
4/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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