Problem Statement:

With the rapid pace of business operations, there is an increasing need for timely data analysis to aid decision-making. Traditional analytical methods often require time, hindering quick business decisions.


The EDA Lab was created as a streamlined platform to perform Exploratory Data Analysis (EDA) on client-provided data. The lab is tailored to the needs of individual clients, ensuring that the analytical output is pertinent and actionable. With auto-generated reports and a visual dashboard, departments can get an at-a-glance view of the insights, facilitating immediate decisions.


  • Instant Analysis: Real-time processing and report generation.
  • Customization: Tailored analytics based on client needs.
  • Interactive Dashboard: Easy-to-understand visual representation for each department.
  • Seamless Integration: Capability to integrate with other business systems for data ingestion.

Use Cases:

  • Daily Operations: Empower teams to view daily metrics and make operational decisions.
  • Strategic Planning: Use data-driven insights for long-term strategy formulation.
  • Performance Review: Evaluate departmental performance based on key KPIs from the dashboard.
  • Trend Identification: Spot business trends and anomalies to act upon.

Data Science Specific Points:

  • Data Collection: Clients provide the data, which is then reformatted and ingested into the EDA Lab for processing.
  • Data Analysis: EDA techniques such as statistical analysis, data normalization, and feature extraction are employed. Outliers and missing data are treated appropriately to ensure accurate results.
  • Results: The lab produces actionable insights presented in the auto-generated report and dashboard. Insights could range from performance metrics to trend analyses, giving businesses a clear picture of their current status and potential future trajectories.

Technologies Used:

  • Programming Language: Python
  • Frameworks: Pandas, NumPy, Flask (for API services)
  • Visualization Tools: Matplotlib, Seaborn, and Dash by Plotly
  • Deployment: AWS, Docker