Exploring NFL play-by-play data with TimescaleDB - Part 2

Join @miranda_auhl as she continues to explore analyzing NFL data from the 2021 Big Data Bowl on Kaggle. Feel free to join in the fun by first running through our tutorial and blog post on the topic.

Other topics that will be explored include Timescale's continuous aggregates and hyperfunctions, make sure to check out the blog posts and tutorials for those tools as well.

🛠 𝗥𝗲𝗹𝗲𝘃𝗮𝗻𝘁 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀
📌 NFL tutorial ⇒ https://tsdb.co/nfl-data-tutorial
📌 NFL blog post ⇒ https://tsdb.co/hacking-nfl-data-blog
📌 Learn more about hyperfunctions ⇒ https://tsdb.co/hyperfunctions-blog
📌 See the hyperfunctions docs to get started ⇒ https://tsdb.co/docs-hyperfunctions
📌 Ask your questions about our hyperfunctions in the discussion ⇒ https://github.com/timescale/timescaledb

🐯 𝗔𝗯𝗼𝘂𝘁 𝗧𝗶𝗺𝗲𝘀𝗰𝗮𝗹𝗲
At Timescale, we are dedicated to serving developers worldwide, enabling them to build exceptional data-driven products that measure everything that matters. Analyzing this data across the time dimension ("time-series data") enables developers to understand what is happening right now, how that is changing, and why that is changing. We are backed by top-tier investors with a track record of success in the industry.

💻 𝗙𝗶𝗻𝗱 𝗨𝘀 𝗢𝗻𝗹𝗶𝗻𝗲!
🔍 Website ⇒ https://tsdb.co/homepage
🔍 Slack ⇒ https://slack.timescale.com
🔍 GitHub ⇒ https://github.com/timescale
🔍 Twitter ⇒   / timescaledb  
🔍 Twitch ⇒   / timescaledb  
🔍 LinkedIn ⇒   / time.  .
🔍 Timescale Blog ⇒ https://tsdb.co/blog
🔍 Timescale Documentation ⇒ https://tsdb.co/docs

📚 𝗖𝗵𝗮𝗽𝘁𝗲𝗿𝘀:
⏱ 1:31 ⇒ Agenda
⏱ 4:35 ⇒ Part 1: Recap on the data
⏱ 8:16 ⇒ Part 2: Queries from last time
⏱ 10:45 ⇒ Part 3: Running some queries
⏱ 31:06 ⇒ Part 4: More complex continuous aggregates
⏱ 42:53 ⇒ Part 5: Hyperfunction and rollups
⏱ 56:29 ⇒ Part 5: Hyperfunction and rollups