Diving Deep into Sensor Data with TimescaleDB | Episode #1: Creating a Sensor Data Pipeline

Timescale Community Templates is a webinar series dedicated to specific industries and designed to foster collaboration and expertise exchange. This webinar is an introduction to the Timescale template for creating a sensors data pipeline. We'll cover the basics of setting up your data pipeline to ensure a smooth and efficient process for handling sensor data.

Recognizing the pivotal role of sensors in IoT, manufacturing, energy, and health, our next chapter focuses on these domains. Sensors generate vast amounts of time-series data, presenting both opportunities and challenges in data management and utilization. To address this, we're hosting four live sessions dedicated to building a strong foundation for working with sensor data using TimescaleDB.

📹 Other Sensor Data Sessions:
✨ Episode 1 - Creating a Sensor Data Pipeline ⇒ (current)

🛠 𝗥𝗲𝗹𝗲𝘃𝗮𝗻𝘁 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀

🐯 𝗔𝗯𝗼𝘂𝘁 𝗧𝗶𝗺𝗲𝘀𝗰𝗮𝗹𝗲
Timescale is a mature, PostgreSQL cloud, specialized for demanding workloads like time series, events, analytics, vectors, and AI. Timescale is dedicated to serving software developers and businesses worldwide, enabling them to build the next wave of computing.

💻 𝗙𝗶𝗻𝗱 𝗨𝘀 𝗢𝗻𝗹𝗶𝗻𝗲!

📚 𝗖𝗵𝗮𝗽𝘁𝗲𝗿𝘀
⏱ 0:00 ⇒ Introduction
⏱ 5:39 ⇒ Part 1: Minimal structure / Hypertables
⏱ 8:02 ⇒ Part 2: Community model by F. Etchezar (installation, signal, sample, query)
⏱ 24:58 ⇒ Part 3: More examples (generic metrics system, data input flexibility, data lifecycle flexibility, data type flexibility)
⏱ 29:15 ⇒ Part 4: Options
⏱ 29:40 ⇒ Part 5: Template Overview: Add Sensors Kickoff
⏱ 33:22 ⇒ Part 6: Chunk time interval (Compression, Compression policies, Hierarchical Continuous Aggregates)
⏱ 41:50⇒ Part 7: Performance tradeoffs
⏱ 43:35 ⇒ Outro

[JR-gylh]

This is awesome. Hope you can do more deep dives on sensor data using TimeScale

[BabaykaMoscow]

How would you make continuous aggregate if data is stored in jsonb and differs from sensor to sensor? Imagine I have one sensor with temperature and humidity and another one with wind speed & wind direction. All the data is kept in a flexible struct fashion as jsonb. Is it possible to create 1 hour continuous aggregate with avg, min & max out of this data? Thanks!