Vol. 2 No. 4 (2025): Issue Month: April, 2025
Articles

Data Analysis For Bikes Dataset Using Tableau

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  • Kolanu Raviteja,
  • Deekonda Santhosh,
  • Majjiga Varshith Yadav,
  • Dr. Diana Moses
Kolanu Raviteja
UG Scholar Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad, India.
Deekonda Santhosh
UG Scholar Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad, India.
Majjiga Varshith Yadav
UG Scholar Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad, India.
Dr. Diana Moses
Professor, Department of CSE, Methodist College of Engineering and Technology, Hyderabad, India
DOI: https://doi.org/10.61359/11.2206-2524
Categories

Published 2025-04-30

Keywords

  • Digital Signal Processing,
  • Noise Suppression,
  • Noise Estimation,
  • Wiener Filtering,
  • Speech Recognition

How to Cite

Kolanu Raviteja, Deekonda Santhosh, Majjiga Varshith Yadav, & Dr. Diana Moses. (2025). Data Analysis For Bikes Dataset Using Tableau. International Journal of Advanced Research and Interdisciplinary Scientific Endeavours, 2(4), 631–641. https://doi.org/10.61359/11.2206-2524

Copyright (c) 2025 International Journal of Advanced Research and Interdisciplinary Scientific Endeavours

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

This dataset contains 150 records of motorcycle sales across different locations. It includes 11 attributes, such as Bike_ID, Date, Location, Brand, Model, Bike_Name, CC (engine capacity), Dealer, Price, Units_Sold, and Total_Revenue. The dataset captures sales transactions from various motorcycle brands like KTM, Kawasaki, Harley-Davidson, Yamaha, and BMW, recorded in multiple cities, including London, Toronto, and New York. Each record represents a unique bike sale with details on pricing, the number of units sold, and the total revenue generated. Additionally, the dataset provides insights into customer preferences, popular bike models, and the impact of different pricing strategies on sales performance. It enables businesses to analyze dealership effectiveness, assess regional demand variations, and identify high-performing models. This dataset can be used for sales analysis, market trends, brand performance evaluation, and revenue forecasting, making it a valuable resource for motorcycle manufacturers, dealers, and market analysts looking to optimize their strategies and improve profitability.

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