Event Impact Analytics Dashboard

An interactive analytics dashboard that correlates news sentiment with financial market behaviour using Python, Streamlit, and Plotly.

A data analytics pipeline that collects news and financial data via APIs and web scraping, processes and cleans it with Pandas and SQLite, applies sentiment analysis to evaluate event-driven market impact, and surfaces insights through an interactive Streamlit and Plotly dashboard.

Tech Stack

PythonPandasscikit-learnPlotlyStreamlitSQLiteAPIs

Features

Automated data collection via public APIs and BeautifulSoup web scraping
Data cleaning and trend analysis with Pandas and SQLite
Sentiment analysis pipeline to evaluate event impact on market behaviour
Interactive dashboard built with Streamlit and Plotly
Correlation analysis between news events and financial metrics

Challenges

Aligning noisy, heterogeneous news and financial datasets on a common time axis.
Choosing and tuning a sentiment model suited to financial news language.
Keeping the Streamlit dashboard responsive under large dataset queries.
Handling rate limits and schema changes from third-party APIs.

Learnings

Practical experience with end-to-end data engineering: ingestion, cleaning, storage, and visualisation.
Applied NLP techniques for domain-specific sentiment classification.
Streamlit and Plotly for building production-quality interactive analytics tools.
Effective use of SQLite for lightweight, file-based analytical storage.

Links

Live Github