International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 11 | Nov 2024
p-ISSN: 2395-0072
www.irjet.net
ECONOMIC DATA ANALYSIS AND SECTOR WISE FORECASTING USING USER-DRIVEN TOOLKIT Austin Indrapaul A 1, Gokuldhev M 2 1PG student, Dept. of Computer Science & Engineering, Vel tech University, Chennai, India
2 Ass. Professor, Dept. of Computer Science & Engineering, Vel tech University, Chennai, India
---------------------------------------------------------------------***--------------------------------------------------------------------1.1 EXISTING SYSTEM Abstract - Economic data analysis plays a crucial role in various aspects of decision-making, policy formulation, and understanding the state of the economy. This project introduces a sophisticated no-code solution tailored for comprehensive data analysis and visualization. This innovative initiative is designed to empower users to gain insights on data, without the need of writing a code. By leveraging these we will analyze economic data for a country and create an AI model which uses real time information. Through the integration of some advanced technologies such as React, Flask, and Python, our web-based application delivers an interactive and user-friendly platform for conducting in-depth analysis on this dataset by end users. The bull or bear run of sectors such as real estate, energy, FMCG etc. can be forecasted with the analyzed data using the AI model. The app will feature MVC architecture to improve scalability and easier maintenance. This project can help to understand a country's economic position, movement, pattern and its impact on various sectors based on several factors, and it can predict the future trends.
The existing system for economic data analysis typically involves the use of statistical software like R or Python. In this system, professionals with expertise in economics, finance, or data analysis are required to write code to manipulate and analyze economic data. They use programming languages to perform tasks such as data cleaning, transformation, statistical modeling, and visualization. This approach requires a strong understanding of programming concepts and statistical techniques, making it more suitable for individuals with technical backgrounds. The existing system often involves a steep learning curve for non-technical users who may not have the necessary programming skills or domain knowledge. Disadvantage: Models trained with historic data can be less effective and adding diverse datasets to the pretrained model can be challenging. Also, the existing software can be complex for the individuals without a technical background.
1.2 PROPOSED SYSTEM
Key Words: Data Analysis, Economic Dataset, Forecasting, Sector Analysis, No-Code App
This project aims to simplify the process and make it more accessible to non-technical users. It would involve the development of a user-friendly interface or platform that allows users to perform economic data analysis without writing code. The proposed system would provide intuitive tools and functionalities that enable users to manipulate, analyze, and visualize economic data using a visual interface. This could include features such as drag-and-drop functionality, pre-built analysis templates, interactive visualizations, and automated data cleaning and transformation processes.
1.INTRODUCTION Economic data analysis plays a crucial role in understanding and making informed decisions about the economy. The objective is to remove barriers for individuals who may not have programming or data science skills but still want to perform analysis on economic datasets. The solution will offer a user-friendly interface that allows users to select the desired dataset, choose the analysis they want to perform, and generate insights and visualizations without writing any code. The project operates within the domain of Data analysis and Machine learning through a web application. To ensure accurate and reliable analysis, the project will prioritize data processing and transformation operations. Visualization will enable users to explore and interact with the charts to gain a deeper understanding of the economic data. It has wide-ranging applications in policy making, business analysis, financial services, academic research, non-profit organizations, economic forecasting, and risk assessment. With the help of advanced technologies, this toolkit will make economic data analysis more accessible and user-friendly.
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Impact Factor value: 8.315
Advantages: The goal of the proposed system is to empower users with limited technical skills to conduct economic data analysis efficiently and effectively, without the need for extensive programming knowledge. The analysis performed will be completely user-driven, based on the user’s needs the model can be tuned and it provides a personalized feel for the user.
2. METHODOLOGY For this application, MVC architecture is followed, the MVC (Model-View-Controller) architecture is a design pattern
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