How to explore TimescaleDB using simulated IoT sensor data

The Internet of Things (IoT) is a trend where computing is becoming ubiquitous and embedded in physical things to collect sensor data about the environment. TimescaleDB is a time-series database that can handle this type of data, which is generally time-series in nature with relational metadata. The tutorial explores the features and capabilities of TimescaleDB using an IoT sensor dataset meant to simulate a real-world IoT deployment. It starts by creating a new TimescaleDB instance via Timescale Cloud and setting up two tables: `sensors` and `sensor_data`. The `sensor_data` table is then populated with simulated data for four sensors, recording data every 5 minutes for the past 24 hours. Basic queries are run to calculate the average temperature and CPU by 30-minute window, and later to get the last temperature value in each period. Finally, a continuous aggregate view is set up to recompute the query automatically at regular time intervals and materialize the results into a table, speeding up the query significantly.