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dbt™ Data Modeling Challenge - NBA Edition

Welcome to the Paradime dbt™ Data Modeling Challenge - NBA Edition!

Table of Contents

1. Getting Started
   • Registration and Verification
   • Account Set-Up
   • Paradime Account Configuration
   • Kickstart Your Project
2. Competition Details
3. Building Your Project
4. Example Submission

Getting Started

Step 1: Registration and Verification

• Submit Your Application: Fill out the registration form.
• Verification by Paradime: We'll review your application against the participation requirements.

Step 2: Account Set-Up

After verification, you'll receive two emails from Paradime:

1. Snowflake Account Credentials: Contains your Snowflake account details. Search for an email with the subject line "Start Your NBA Data Modeling Challenge – Your Snowflake Credentials."
2. Paradime Platform Invitation: An invitation to access the Paradime Platform. Search for an email with the subject line "Final Step: Activate Your Paradime Account for the NBA Challenge."

Step 3: Paradime Account Configuration

• Access Paradime: Use the provided credentials to log into your account. Join the Paradime workspace using the invite email.
• Snowflake Integration: Add Snowflake credentials (Username, Password, Role, Database) to Paradime.
• Act Fast - Limited Time Activation: The links to activate your Paradime account expire within 24 hours!

Step 4: Kickstart Your Project

• Create a New Branch: Open the Paradime Editor and create a new branch. Your branch name should follow this format: "nba-<your_email>"
• Start Developing: Begin crafting SQL queries, developing dbt™ models, and generating insights!

Need Help?: Join the #nba-challenge channel on Slack for assistance.

Competition Details

• Entry Requirements
• Competition Deliverables
• Judging Criteria

Building Your Project

Now that you're set up, you have until March 8, 2024 to complete and submit your project!

Step 1: Getting to Know the Paradime Editor

• Using the Editor
• Working with Git
• Creating Your First dbt Model

Step 2: Getting to Know the NBA Data Sets

Explore 7 NBA data sets provided by Paradime, each with primary and foreign keys for insightful analysis. Detailed information about each dataset is available in the staging files and YAML file. If reading YAML file is confusing, you can learn about each data set and columns in within the Paradime Catalog UI

Step 3: Generating Insights

Your goal is to build dbt™ models that reveal compelling insights for NBA fans and General Managers. Here are some suggested topics:

• Best second-round draft picks and international players.
  • Data Required: common_player_info, player_game_logs
• NBA teams' spending efficiency.
  • Data Required: team_spend_by_season, team_stats_by_season
• Players' playoff vs regular season performance.
  • Data Required: player_game_logs
• Worst plus/minus in NBA history.
  • Data Required: player_game_logs
• Overpaid NBA players.
  • Data Required: player_salaries_by_season, player_game_logs
• Worst regular season teams to win NBA finals.
  • Data Required: team_stats_by_season

Creating Data Visualizations

Choose any data visualization tool. Paradime has various BI tool integrations like Power BI, Lightdash, Metabase, Preset, Tableau, Metabase, and Looker.

Alternatively, Alternatively, export the data behind your dbt™ models from Snowflake to .csv files. Note: We'll verify if the .csv export matches your dbt™ models. [Add screenshot]

Submitting Your Project

Submission deadline: March 8th, 2024 Submit the following to Parker Rogers (parker@paradime.io) upon completion:

• A GitHub repository containing your dbt™ models (Example)
• A README.md narrating your project's story and methodology (Example)
• Data visualizations and analyses, ideally in your README.md or through alternative formats (Example)

Example Submission

Here's an example project that fulfills all requirements and would be elligble eligible for cash prizes. Feel free to use this template for your submission, but ensure your insights are unique!

Table of Contents

1. Introduction
2. Data Sources
3. Methodology
   • Tools Used
   • Applied Techniques
4. Visualizations
   • Team Playoff Appearances
   • Player Playoff Games
   • Top Playoff Scorers
   • Top Regular Season Scorers
   • NBA Players by University
5. Conclusions

Introduction

Explore my project for the dbt™ data modeling challenge - NBA Edition, Hosted by Paradime! This project dives into the analysis and visualization of NBA statistics, designed for basketball enthusiasts and analysts.

My GitHub repo

Data Sources

My analysis leverages three key NBA datasets from Paradime:

• PLAYER_GAME_LOGS
• TEAM_STATS_BY_SEASON
• COMMON_PLAYER_INFO

Methodology

Tools Used

• Paradime for SQL, dbt™, and CSV exports.
• Snowflake for data storage and computing.
• Google Sheets for data visualization.

Applied Techniques

• SQL and dbt™ to transform stg_player_game_logs into seasonal player statistics
• SQL and dbt™ to transform stg_player_game_logs and stg_common_player_info to understand playoff and regular season performance by individual players
• SQL and dbt™ to transform stg_common_player_info for insights on NBA players' college backgrounds.
• SQL and dbt™ to transform stg_team_stats_by_season for insights on NBA Teams' historical playoff performance.

Visualizations

Team Playoff Appearances

Visualization of playoff appearances for all 30 NBA teams, including their playoff appearance rates.

Insights: The Los Angeles Lakers' dominance in playoff appearances, and the San Antonio Spurs' highest playoff appearance rate. The Spurs have only missed the playoffs 9 times!

Player Playoff Games

Assessment of NBA players with the highest number of playoff game wins and their win percentages. The '*' next to NBA Player name indicates if they're a member of the NBA Greatest 75 Team

Insights: LeBron James has the most playoff wins of any player, but here's what's most interesting: Of the 25 players with the most playoff wins, only 12 of them are members of the NBA Greatest 75 team. There are several players listed that impact playoff wins and compliment their team's best players, but aren't known as on the the all time greats, such as: Derek Fisher, Robert Horry, Danny Green.

Top Playoff Scorers

Showcases players who achieved the the most points scored in any playoff season.

Insights: Michael Jordan, LeBron James, and Kobe Bryant are the only players having three seasons within the top 25 highest most points scored in a playoff season.

Top Regular Season Scorers

Highlights NBA players who scored the most in regular seasons.

Insights: Wilt Champerlain is one of the best regular season scorer of all time. In addition to having the most points scored in any regular season ever (4,029), he also has six season in the top 25. The only other player with 6 top 25 seasons is Michael Jordan. In the chart above, notice that Wilt Champerlain doesn't appear once in the top 25 playoff scorers of all time 👀.

NBA Players by University

Displays which universities have produced the most NBA players.

Insights: Kentucky has produced the most NBA players in NBA history by a significant margin.... Go Wildcats!

Conclusions

This project offers key insights for NBA enthusiasts, such as: This project successfully extracts significant insights from NBA data that NBA fans would find interesting, such as:

• The dominance of teams like the Los Angeles Lakers and the San Antonio Spurs in playoff appearances
• The critical role of "role" players, as highlighted by the playoff games by player insights,
• The extraordinary achievements of players like LeBron James, Michael Jordan in he playoffs, and Wilt Chamberlain in the regular season.
• The influence of universities like Kentucky in producing NBA talent.