Real World Projects
Table of Contents
Real World Projects Project 1: Large-Dataset-Generation Breakdown of Project 1 Project 2: Data-Analysis-and-Interpretation Breakdown of Project 2
Real World Projects
Project Description: Generates large dataset from News API
Programming Languages: JavaScript, Node.js, and Axios
Programming Tools: News API, Visual Studio Code, Git, and GitHub
Start Date: August 4, 2024
End Date: August 6, 2024
Breakdown of Project 1
Strengths:
Clear documentation: README well structured, good explanation of project’s purpose, setup, and usage
Specific use: Project has a specific use (generating large dataset from News API)
Technologies Used: Project uses popular and widely used technologies (Node.js, JavaScript, and Axios)
Weaknesses:
Limited customization: Project is only designed for a specific case (fetching articles about Elon Musk). Adjust to adapt to other use cases.
Dependence on News API: Project relies heavily on the News API which creates limitations (rate limit, data quality, possible change to API endpoint)
Data storage: Project stores data in text file, not suitable for large-scale data storage/analysis
Potential for real-world/company use:
Media monitoring: Companies can use to monitor news articles about their brand, competitors, or industry trends
Market research: Researchers can use to gather data on market trends, customer opinions, or product reviews
Data analysis: Data analyst can use as starting point for more complex analysis tasks (sentiment, topic modeling)
Improvements for real-world/company use:
Add customization options: Allow users to specific their own API (endpoints, query parameters, data storage location)
Improve data storage: Consider using more robust data storage location (database, data warehousing)
Enhance error handling: Add more robust error handling to make sure project can handle API errors, network issues, etc
Project Description: Data analysis and interpretation project that uses R to analyze and evaluate news article data
Programming Languages: R
Programming Tools: News API, Replit, and GitHub
Start Date: August 4, 2024
End Date: August 8, 2024
Breakdown of Project 2
Strengths:
Clear methodology: Project follows clear defined methodology (makes it easy to understand, replicate)
Organized code: Code is organized (tasks separated, clear sections)
Effective data visuals: Bar plot, effective way to show findings (clear title, labels- easy to understand)
Data exploration: Project has data exploration steps (view structure of data frame, checking missing values)
Weaknesses:
Limited data validation: Project does not have data validation steps (leads to - errors, inconsistencies in data)
Limited data cleaning: Project does not have data cleaning steps (leads to - errors, inconsistencies in data)
Limited data transformation: Project does not have data transformation steps (difficult to analyze data)
Limited reproducibility: Project does not have any steps to make results more reproducible (setting random seed, robust method generating plot)
Potential for real-world/company use:
Analyzing Customer Feedback: Company use project’s methodology analyze (customer feedback, identify trends, and patterns in satisfaction)
Monitoring Website Traffic: Analyze website traffic data, identify trends, and patterns of user behavior
Analyzing Sales Data: Analyze sales data, identify trends, and patterns in sales performance
Improvements for real-world/company use:
Data Validation Steps: Add validation steps, ensure data is in expected format (no errors in data)
Data Cleaning Steps: Include data cleaning steps to handle missing values, inconsistent data
Methodology: Include advanced data analysis and visualization techniques
Results Reproducible: Add steps for results more reproducible
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