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Analyze and transform raw tweets into interactive visualizations to derive actionable insights using the Twitter API.
In today's data-driven world, businesses rely heavily on social media analytics to extract valuable insights from platforms like Twitter, making it a crucial skill for entry-level data analysts and engineers. In this Build Project, you'll wear the hat of a Business Intelligence Analyst and develop a pipeline to analyze and transform raw tweet data into interactive visualizations for actionable insights. Under the supervision of an experienced industry expert, you'll fetch Twitter data via the API, preprocess and clean it, and visualize trends and patterns using tools like matplotlib, seaborn etc. You'll become familiar with industry tools and methodologies like Python, data wrangling, and data visualization techniques. All this will happen in an environment that simulates the operations of a real analytics team, preparing you for the fast-paced world of data analysis and visualization.
Who are we? What are our career interests? What industry tendencies attract your attention the most? What will our project look like? What does the final deliverable looks like?
You will set up your Twitter API keys and GitHub repository, and learn the basics of APIs and Python to prepare for the project.
You will learn how to use the tweepy library to authenticate with the Twitter API and fetch tweets based on a user-defined query or hashtag.
This workshop will cover basic pandas operations like filtering and selecting columns. You will also clean tweets to prepare the data for analysis.
This workshop will cover creating visualizations that provide actionable insights into our data.
In this session, you will learn how to export your Jupyter notebooks to various formats (e.g., HTML, PDF) for sharing and presentation. You will also be introduced to Git for version control, learning how to initialize a Git repository, commit changes, and push your notebook to GitHub. This will ensure your work is properly saved and version-controlled.
This session will be a dedicated time for you to review the entire project. You will have the opportunity to ask clarifying questions, and troubleshoot any issues. Finalize code, share for feedback and start designing presentation.
In this final session, you will present your completed projects, demonstrating your visualizations, and how you used Git for version control. You will submit your projects to GitHub, ensuring they include a well-documented README.md file and a final discussion on lessons learned.
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Shruti Adoni is a Business Intelligence Build Fellow at Open Avenues Foundation, where she works with students leading projects in Business Intelligence.
Shruti is a Data Engineer at Citadel Securities, where she focuses on building and maintaining data pipelines and infrastructure to support Salesforce team's integration and analytics needs. Her role also involves providing clean, structured data for analytics and reporting while collaborating with cross-functional teams to address business needs. Additionally, she prioritizes compliance, security, and performance optimization to handle large-scale data efficiently and securely.
Shruti has over three years of experience in the Business Intelligence field. Previously she worked as a business analyst at GE Appliances
She holds a Masters in Business Analytics.
A fun fact about Shruti is that she speaks 5 languages!