Opportunity brief
Overview:
This is a build-and-analysis-focused Data Analytics Hackathon designed for students, aspiring analysts, data professionals, and problem-solvers who want to turn raw data into meaningful insights and actionable recommendations.
What You'll Do:
On 6th September, participants will work with a real-world dataset provided by the organizers and perform an end-to-end data analysis by:
- Understanding the business problem and dataset.
- Cleaning, transforming, and preparing the data.
- Exploring patterns, trends, and relationships.
- Performing quantitative and statistical analysis.
- Building meaningful visualizations and dashboards.
- Identifying key insights and actionable recommendations.
- Presenting your analysis and findings.
The challenge is centered around using data to solve real-world problems by turning raw datasets into clear insights and data-driven decisions.
By the end of the Hackathon, you'll have a complete analysis project that can be showcased in your portfolio, discussed during interviews, or further developed into a real-world analytics solution.
Who Can Participate?
- Individuals and teams are welcome.
- Recommended team size: Max 2 members & Individualy can also Participate.
- Beginners and experienced analysts can participate.
- Participants can use Python, SQL, Excel, Power BI, Tableau, and other analytics tools.
Project Requirements:
Every team must:
- Perform the analysis using the dataset provided during the event.
- Clearly document the analysis process and methodology.
- Explain the problem statement, approach, findings, and recommendations.
- Submit a complete and functional analysis with supporting visualizations.
Submission Checklist:
To complete your submission, provide:
- Final analysis report or presentation.
- Dashboard and/or data visualizations.
- Source code/notebook or analysis file, where applicable.
- Brief explanation of the methodology and key findings.
- Key insights and actionable recommendations.
Rules & Judging Criteria:
Event Rules:
- Participants must use the dataset provided by the organizers.
- Pre-built analyses or previously completed projects are not permitted.
- External tools, libraries, and publicly available resources may be used.
- Any form of plagiarism or unauthorized copying will result in disqualification.
- Participants must disclose the use of AI tools in their analysis or submission.
- All submissions must be completed and submitted before the official deadline.
Evaluation Areas:
Projects will be assessed based on:
- Data cleaning and preparation.
- Analytical approach and problem-solving.
- Quality and accuracy of insights.
- Data visualization and storytelling.
- Depth of analysis.
- Business relevance and actionable recommendations.
- Overall presentation and completeness.
Turn data into insights, uncover the story behind the numbers, and show how analytics can drive better decisions.