Start exploring OmicIDX on the Bigquery web console

Gain familiarity with the Bigquery cloud console when working with the OmicIDX dataset.

Bigquery most closely resembles a [relational database management system]. Roughly speaking, the data in Bigquery are stored as records where each record can be thought of as a set of values for a number of pre-defined columns. An individual column can contain complex or nested data.
Bigquery is a cloud-based. Cloud-based implies that the system is supported and maintained by someone else, in this case, Google. In addition, the Bigquery system scales automatically and transparently and can adjust to workloads of nearly arbitrary size. From our point-of-view, Google provides us with a database system that allows us to load, query, modify, and delete data as we see fit.
Bigquery stores data as columns. This has implications for database efficiency and design, but for us, this means that we can reduce costs and potentially increase performance of our queries by limiting those queries to only the columns we need. In other words, instead of SELECT * FROM TABLE, we should focus queries to the columns of interest (SELECT col1, col2 FROM TABLE).
Bigquery benefits from denormalization. The implications of #3 lead to a desired schema that includes repeated values rather than splitting those values into separate tables.

For some more interesting facts and tips on using Bigquery, see “Twelve Truths about Bigquery”.

Accessing OmicIDX

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