Get Started with Google Cloud — selected guide
Locating and querying public datasets
Twelve practical entries spanning docs, networking, storage, IAM, cost, data, workflows, and APIs
Twelve 2018–2022 introductions use small tasks to explain networking, persistent storage, access control, BigQuery queries and cost limits, object versions, sensitive-data inspection, workflow orchestration, and speech transcription.
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BigQuery's public datasets let you practice SQL analysis or combine shared records with your own data without importing a copy first. This walkthrough uses American Community Survey housing data to examine rent as a share of income in King County. 00:01–03:10(opens in a new tab)
Key Points Covered
- Inspect a table before querying it. The dataset listing describes the data and its update frequency. Opening a table reveals its schema—the available columns—along with its size, row count, and sample rows. 01:03–02:06(opens in a new tab)
- Start from a question or a sample query. The demonstrated query asks how rent as a percentage of median income changed from 2011 to 2017. Its result breaks that comparison down by ZIP code, rather than returning a single county-wide figure. 02:06–03:10(opens in a new tab)
- The video presents the BigQuery sandbox as a way to start within the free tier and points to the then-named Data Studio for visualization without writing SQL. 02:06–03:10(opens in a new tab)
Full video: https://www.youtube.com/watch?v=4-rZd5DwEww(opens in a new tab)