dbt™ Data Modeling Challenge - Fantasy Football Edition

Welcome to the dbt™ Data Modeling Challenge - Fantasy Football Edition! This global hack-a-thon invites you to transform raw fantasy football data into insightful, data-driven insights. You'll use Paradime, Snowflake, and Lightdash to model, explore, and visualize data—showcasing your analytics engineering expertise and vying for prizes up to $1,500.

📋 Table of Contents

1. Getting Started
   • Registration and Verification
   • Account Setup
   • Support and FAQs
2. Competition Details
3. Tools and Resources
4. Building Your Project
5. Additional NFL Data
6. Submission Guidelines
7. Judging Criteria
8. Prizes
9. Example Submission

🏈 Getting Started

Registration and Verification

Make sure you meet the Entry Requirements before registering

• Register: Complete the registration form
• Verification: Paradime will review your application. If approved, you'll receive credentials via email to begin.

Account Setup

After approval, you'll receive two emails:

1. Snowflake Account Credentials: Contains your Snowflake account details. Search for "Snowflake Credentials: dbt™ Data Modeling Challenge - Fantasy Football Edition."
2. Paradime Platform Invitation: An invitation to access the Paradime Platform. Search for "[Paradime] Activate your account."

Additional Guidance: Detailed setup tutorials will be provided in your Snowflake confirmation email.

Support and FAQs

• Slack Community: Join #fantasy-football-challenge on Paradime's Slack
• Additional Questions: Check documentation or ask in Slack
• Troubleshooting Emails: Search for "mail@paradime.retool-email.com" in your registration email

🏈 Competition Details

Key Dates:

• Start: January 2, 2025
• Submission Deadline: February 4, 2025, 11:59 PM PT
• Winners Announced: February 6, 2025 (right before the Superbowl!)

Who Should Participate?

• Data Analysts, Analytics Engineers, Data Engineers, Data Scientists, and SQL/dbt™ enthusiasts
• Individual submissions only (no teams)
• Experience with SQL, dbt™, Git, and basic data visualization required

⚙️ Tools and Resources

1. Paradime

   • SQL, dbt™ development, and AI-assisted analytics engineering
   • Documentation | Code IDE Tutorial | Commands Panel | DinoAI Tutorial

2. Lightdash

   • Open-source BI for dbt™ metrics and visualizations
   • Documentation | Tutorial

3. Snowflake

   • Cloud data platform for storage and compute

4. GitHub

   • Version control and project submission platform

🛠 Building Your Project

Need a Spark of Inspiration?

Check out these resources:

• Winning Strategies for Paradime's Movie Data Modeling Challenge: Learn the strategies, best practices, and insights uncovered from winning participants in previous Data Modeling Challenges.
• Explore winning submissions from Paradime's recent Data Modeling Challenges:
  • Bruno De Lima's Submission: 1st Place winner from Paradime's dbt Data Modeling Challenge - Socal Media Edition.
  • Spence Perry's Submission: 1st place winner from Paradime's dbt Data Modeling Challenge - NBA Edition.
  • Isin Pesch's Submission: 1st place winner from Paradime's dbt Data Modeling Challenge - Movie Edition.

Step 1: Master Required Tools

• Explore Paradime's code IDE, AI development, data explorer, and lineage tools
• Understand Snowflake schemas and tables in your fantasy football datasets
• Learn to connect dbt™ models and build Lightdash dashboards

Step 2: Explore and Enhance the Data

• Examine pre-loaded fantasy football datasets
• Consider external data sources to enhance analysis (injury reports, game results, weather conditions, draft prospects, depth charts, etc.)

Step 3: Generate Insights

Uncover NFL insights related to fantasy football—the possibilities are endless!

Potential Insight Areas with Pre-Loaded Datasets:

• Top Performers by Week/Season: Using player_stats_by_game, identify highest-scoring players each week and over the season.
• Team Defense Impact: Using play_by_play, determine which defenses give up the most fantasy points by position.
• Red Zone Efficiency: Using play_by_play, pinpoint which players or teams excel in scoring opportunities inside the 20-yard line.

Potential Insight Areas with External Datasets:

• Top scoring players by week/season
• Player consistency analysis (boom/bust metrics)
• Impact of team matchups on player performance
• Identifying players with high injury propensity
• Forecasting 2025 draft prospects

Step 4: Visualize with Lightdash

• Create clear, informative dashboards w/ written conclusions
• Use dbt™ models as metric sources (optional)
• Ensure visualizations support your conclusions

🌟 Additional NFL Data

If you want to pull additional NFL data for your analysis, you can use the nfl_data_py library, the same tool we used to pre-load datasets into Snowflake:

• GitHub Repo: nfl_data_py

For reference, the scripts we used to load the pre-loaded datasets can be found in the Scripts folder of this repository.

📤 Submission Guidelines

Deadline: February 4, 2025, 11:59 PM PT

Submission Process:

1. Complete your dbt™ project in Paradime
2. Build Lightdash visualizations
3. Commit code, documentation, and README.md to GitHub
4. Email parker@paradime.io:
   • Subject: "<Your_Name> - Fantasy Football Data Modeling Challenge Submission"
   • Include GitHub branch link

Need help? follow this step-by-step tutorial to submit your project.

🎯 Judging Criteria

A panel of five independent judges will assess each submission based on the following categories. Each category is scored on a scale of 1-10:

1. Value of Insights: Are the findings relevant and valuable for fantasy football analysis?
2. Complexity of Insights: Do you connect multiple datasets and implement advanced transformations?
3. Quality of Materials: Is your code clean, your dbt™ models well-structured, and your visualizations high-quality?
4. Integration of New Data: Have you effectively incorporated additional datasets to enhance your analysis?

🏆 Why Join This Challenge?

• Showcase Your Skills: Demonstrate your SQL, dbt™, and analytics engineering expertise.
• Work with Modern Tools: Gain hands-on experience with Paradime, Snowflake, and Lightdash.
• Build Your Portfolio: Enhance your professional profile with a compelling analytics project.
• Network: Connect with a community of data professionals and industry experts.
• Win Prizes: Compete for Amazon gift cards worth up to $1,500!

Prizes:

• 1st Place: $1,500 Amazon gift card
• 2nd Place: $1,000 Amazon gift card
• 3rd Place: $500 Amazon gift card

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Example Submission Template

For guidance on what a successful submission may look like, check out examples from previous dbt™ Data Modeling Challenge winners.

Table of Contents

1. Introduction
2. Data Sources
3. Methodology
4. Visualizations
5. Insights
6. Conclusions

Introduction

[Brief overview: What you aimed to achieve and why it matters] [Include link to Lightdash dashboard]

Data Sources

• [Fantasy Football Data (Snowflake)](... link or details ...)
• [Additional Data Set 1] - [Description]
• [Additional Data Set 2] - [Description]

Methodology

Tools Used

• Paradime for dbt™ modeling and SQL
• Snowflake for data warehousing
• Lightdash for visualization
• [Any other tools/techniques used]

Applied Techniques

[Discuss transformations, tests, and models built]

Visualizations

[Include screenshots or links to Lightdash dashboards]

Insights

[Detail your findings, supported by data and visuals]

Conclusions

[Summarize key takeaways and recommendations]