Parker Rogers on LinkedIn: Winning Strategies for Paradime's Movie Data Modeling Challenge (2024)

Woot woot! Thanks for joining Jessica Cherny !

4

The 𝒅𝒃𝒕™ 𝑫𝒂𝒕𝒂 𝑴𝒐𝒅𝒆𝒍𝒊𝒏𝒈 𝑪𝒉𝒂𝒍𝒍𝒆𝒏𝒈𝒆 - 𝑴𝒐𝒗𝒊𝒆 𝑬𝒅𝒊𝒕𝒊𝒐𝒏 is LIVE!And the submission deadline is May 26th, so go ahead and register! This cheeky video will give you all the ins and outs of the competition. You’ll learn how it works, what you’re expected to build, and how to win the big prizes.Register here 👉 https://bit.ly/3JvSlpqSide note - It's been a blast building this whole competition with paradime.io and Lightdash!

20

3 Comments

🗣️ Calling all data and analytics enthusiasts! Ready to showcase your skills? Lightdash and paradime.io invite you to join the second edition of our dbt™ data modeling challenge - this time, we're heading to the cinema! 🍿🎥Flex your SQL querying prowess, construct dbt™ models, and uncover valuable insights for a chance to win a $1,500 Amazon gift card! Don’t miss out - competition starts today! See details and sign up below 👇https://lnkd.in/gA-QdgnA

22

1 Comment

István Mózes' blog is an absolute goldmine for interested in building advanced statistical metrics with SQL and dbt™.His metrics are built from historical NBA datasets, but his process and best practices extend far beyond basketball!Here are some of my favorite metrics he build:- Offensive Efficiency: This statistic quantifies a team's scoring ability per 100 possessions, offering an insightful measure of offensive prowess, enabling a standardized comparison across teams with differing game paces.- Defensive Efficiency: Measures a team's capability to limit the opposing team's points per 100 possessions, serving as a critical indicator of defensive strength and informing strategy enhancements.- Pace: Estimates the average number of possessions a team has per game, shedding light on how game tempo affects overall performance.Give it a read! 👇

4

1 Comment

He shot his shot and came home with the W! 🏀Our gold medalist in the NBA Data Modeling Challenge, Spence Perry, has just wrote a fascinating blog post (seriously, it's fascinating) detailing his journey through the competition.In it, you'll find:- Strategies for planning and executing data projects- His favored data toolkit (shoutout to Lightdash)- Techniques and best practices for data modeling (using dbt™)- Valuable insights into the NBAGive it a read! 👇

4

1 Comment

Great resource for anyone interested in improving their SQL, dbt™, and data storytelling skill sets!In this blog, Nikita Volynets delves into the details of how he built his high-quality submission for the NBA data modeling challenge. He covers his best practices for project planning, building dbt™ models, and generating insights and conclusions from historical NBA data.My favorite part? With the exception of the 2019 NBA Finals, the Toronto Raptors are the epitome of average 🤣^ I can say that... I'm a Utah Jazz fan!Give it a read!

5

Judging over 20 submissions in paradime.io recent NBA Data Modeling Challenge turned out to be one of the best accidental educations I've ever had.It inspired me to launch a blog series called "NBA Challenge Rewind" — It's a spotlight on the "best of" submissions, highlight the superb minds that crafted them. Imagine having a backstage pass to the top data professionals as they build their projects. That's what each post offers—a journey from the spark of an idea to the polish of the final product, all while soaking up their best practices in #SQL, #dbt, #dataanalysis, #datastorytelling, and #projectplanning.First up in our lineup is Katie Shaffer! Katie's work is a masterclass in efficiency and expertise in SQL development and data storytelling. She's got a knack for demystifying complex SQL queries, making them readable and easy to digest, and turning them into crystal clear data visualizations. Give it a read, and check out the comments for more installments of "NBA Challenge Rewind"!https://lnkd.in/gryDW3uX

18

1 Comment

Maybe AI won't replace us analytics engineers, but one thing's for certain: it's already a game changer in boosting our productivity!Big news this week: Paradime launched 🦖 𝐃𝐢𝐧𝐨𝐀𝐈 🦖! It's our latest AI creation, packed with AI features designed to boost analytics engineering productivity and enhance SQL and dbt™ development. In this quick video, I share various DinoAI features and how they work, such as:📝 𝐂𝐨𝐦𝐦𝐢𝐭 𝐌𝐞𝐬𝐬𝐚𝐠𝐞𝐬: Automatically generate detailed commit messages tailored to your specific code changes, enhancing communication within your team.🧙♂️ 𝐂𝐨𝐩𝐢𝐥𝐨𝐭: An intelligent code generator within your editor, offering custom code suggestions based on your dbt™ project’s structure and content.⚡ 𝐀𝐮𝐭𝐨𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞: Smart autocompletion for SQL and dbt™ code, streamlining the creation of queries, columns, calculations, etc. 💬 𝐂𝐡𝐚𝐭 𝐏𝐚𝐧𝐞𝐥: Similar to ChatGPT, this feature offers real-time assistance for coding questions, directly within the editor.To learn more about DinoAI, check out the blog in the comments! 👇

16

1 Comment

Here's a less-boring Analytics Engineering blog post to end your Friday! paradime.io wrapped up the NBA Data Modeling Challenge last week, and I put together my favorite, participant-generated insights, such as:- How has the 3-pointer dramatically changed the NBA over the last decade- Who are the most consistent playoff performers all time?- Who SHOULD HAVE been awarded MVP each season?- Who are the most clutch NBA players of all time?- Inflation adjusted, who are the highest paid NBA players ever? - In 2022-23, who were most overvalued players?Special shout out to all the participants who's work is highlighted in the blog: Spence Perry, Christopher Hughes, István Mózes, Arın Tazeler, Matthew Tribby, Iker Cámara Bengoechea, Cai Parry-Jones!

13