Loading temperature data to Cloud Bigtable and BigQuery-ing it

Google Bigtable is a fully managed NoSQL service with a focus on low latency and high throughput. It is well suited for storing data for large analytical processing, operation data from IoT devices, other time-series data, and so on. Cloud Bigtable is designed for performance, for huge databases (~1 TB) and it optimizes your data over time. In this recipe, we'll have a look at a small database generated by an IoT temperature sensor. We'll write a Python script to simulate a sensor sending temperature data located in a garden to the  Bigtable. Then, we'll use BigQuery to connect to the Bigtable database to query and make meaning out of the data store.

Getting ready

The following are the initial setup verification steps to be carried out before the recipe can be executed:

1. Create or select a GCP project
2. Enable billing and enable the default APIs (some APIs such as BigQuery, storage, monitoring, and a few others are enabled automatically...