NBA EDITION

dbt™ Data
Modeling Challenge

🏀 Join now 🔥
Attention, analytics and data folks—it's your time to shine! Join Paradime in our hands-on data modeling challenge. Utilize real NBA data to craft SQL queries, develop dbt™ models, and derive insights, all for a chance to win a $1,500 Amazon gift card. 
A silhouette illustration of a basketball player
Using tools that you are already familiar with
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Introduction

At Paradime, we believe in the transformative power of dbt™ and its ability to shape data-driven organizations. That's why we've built a more robust and user-friendly platform to manage every aspect of your analytics engineering lifecycle. Our goal is to empower data professionals like you. This challenge is your platform to showcase your expertise in SQL, dbt™, and analytics, not only to extract meaningful insights from historical NBA data but also to win a $1,500 Amazon gift card!

To better understand how this competition works, check out this introductory video and explore an example of a final project submission.

Excited? Invite a friend (or two), demonstrate your analytics engineering talent, and compete for a chance to win big!
🏀 Join the challenge 🔥

What’s in it for you

Time to put your game face on and demonstrate your SQL, dbt™, and data analytics expertise for a chance to win up to a $1,500 Amazon gift card! Paradime will honor the top three contestants as follows:
#1
$1,500
Amazon gift card
#2
$1,000
Amazon gift card
#3
$500
Amazon gift card
🏀 Join the challenge 🔥
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About the challenge

A whistle-blowing icon represents the start of the challenge.
Let the games begin
February 1, 2024
An alarming alarm clock icon represents the challenge timeline's deadline.
Submission deadline
March 8, 2024
A loudspeaker icon indicates the time of the challenge winner announcement.
Winners announced
March 11, 2024

How it works

When your registration is approved, you'll get access to:
  • Paradime for SQL & dbt™ development.
  • Snowflake Data Cloud for compute and storage, pre-loaded with seven historical NBA datasets.
  • Sigma for dashboards and visualization (not required, but available to participants for free!)
  • GitHub repository with pre-configured models to get you started!
Your mission: Craft insightful analyses and visualizations using SQL and dbt™. You have until March 8, 2024 to complete and submit your project.

Snowflake, Paradime, and Github are required, feel free to incorporate additional tools, techniques, and data to amplify your insights… Go on, get creative!

To better understand how this competition works, check out this introductory video and explore an example of a final project submission.

Challenge details

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Entry requirements

  • Participants must be current or former data professionals (Data Analysts, Analytics Engineers, Data Engineers, Data Scientists, etc.).

  • Solo participation only.

  • Must have hands-on experience with SQL, dbt™, and Git.

  • Participants use, but are not limited to, the following tools:

    • Paradime for SQL & dbt™ development.

    • Snowflake Data Cloud for compute and storage.

    • Sigma for dashboards and visualization (not required, but available to participants for free!)

    • GitHub repository with pre-configured models to get you started.

  • Must be able to explain their code and insights comprehensive. You can use ChatGPT, but you better understand it! 🤣

  • Deadline for submissions: March 8, 2024. Winners to be announced on March 11, 2024.

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Challenge deliverables

Participants are expected to submit:

  • A GitHub repository containing your dbt™ models (Example)

  • A README.md that briefly narrates your project's story — what you've built and your methodology (Example)

  • Data visualizations and associated analyses, ideally incorporated into your README.md or presented through alternative formats (Example)

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Judging criteria

Judges will score each submission based on:

  • Value of findings:
    Are the results relevant to NBA fans and/or NBA General managers?

    • If you’re focusing on insights just for NBA fans (i.e., without practical business application for General Managers), get creative! Discover something fun and accurate that you'd find interesting if you saw it on social media, for example.

  • Complexity of findings:
    Are you creating relationships between datasets and providing in-depth analytical conclusions?

    • Complexity ≠ value, but you should use multiple datasets to generate valuable conclusions.

  • Quality of materials:
    Is your code of professional quality? Are your data visualizations well-designed? Are your insights' conclusions clear to the reader?

    • Your SQL, dbt™, visualizations, and conclusions should be high quality. If it’s not something that you’d be comfortable sharing with your peers, it won’t be good enough for the judges.

💡 Bonus

These won’t be judged as heavily as the criteria above.

Participants are expected to submit:

  • Bring in new data! Remember: you’re not limited to the tools and datasets Paradime has provided.

  • Utilize Paradime features beyond the Paradime Editor (dbt™ IDE). Explore our other features like:

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Judges

A picture of Emily Hawkins, the judge of the data modeling challenge.
(Analytics Engineering,  GlossGenius)
A picture of Jake Hannan, the judge of the data modeling challenge.
(Data Platform, Sigma)
fabio
(Co-founder, Paradime)

Common questions

How can I obtain technical support from Paradime?

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Access our Slack community for 24/7 assistance. For specific tool setup issues (connecting to Paradime, Snowflake, or GitHub), Parker Rogers from Paradime is available for direct support via Zoom.

Is seeking external assistance permitted?

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Definitely. While self-reliance is crucial, utilizing your network, online resources, and even ChatGPT to enhance your project is recommended, as long as you fully understand the concepts and their implementation.

Can I utilize additional tools beyond the required ones?

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Yes, you are free to use any supplementary technologies or methods that enhance your workflow, in addition to the mandatory Paradime, Snowflake, Sigma, and GitHub tools.

Do participants begin from scratch?

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Not at all! Paradime provides the following resources:

  • The Paradime platform for SQL & dbt™ development.

  • The Snowflake Data Cloud for compute and storage.

  • Sigma for dashboards and visualization.

  • A pre-configured GitHub repository to jumpstart your project (example data models included!)

  • Seven comprehensive NBA datasets covering various statistics and information:

    • common_player_info : Contextual information (not statistics!) per player from the 1946-2023 NBA seasons (4.8k rows)

    • games : Statistics per game played from the 1946-2023 NBA seasons (137.6k rows)

    • player_game_logs : Statistics per player per game from the 1946-2023 NBA seasons (1.4m rows)

    • player_salaries_by_season : Annual salary per player, per year from the 1990-2023 NBA seasons (15.5k rows)

    • teams : Contextual information (not statistics!) per team (30 rows)

    • team_spend_by_season : Annual spend per team, per year from the 1990-2023 NBA season (1k rows)

    • team_stats_by_season : Year-by-year statistics for each team during the 1950-2023 NBA season (1.6k rows)

Am I allowed to incorporate additional data sources?

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Incorporating extra data sources is optional but can enrich your analysis and potentially boost your project's success.

Is this event a hackathon?

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No, this is an asynchronous competition without scheduled kick-off meetings, working sessions, or prize ceremonies. Participants work at their own pace.

If I win, how will I receive a gift card?

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Winners will receive an amazon e-gift card via email.

What are some key strategies for developing NBA insights?

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Aim to generate insights appealing to NBA fans and/or General Managers using our seven historical datasets. For inspiration, here are some intriguing insights to explore:

For more examples, Paradime's GitHub repository offers a range of insights, such as the top scorers in playoff seasons, colleges producing the most NBA players, and teams with frequent playoff appearances.

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