The Overall Structure
There are three layers of organization within your BigQuery project:
Project
Dataset
Tables
In this page, we'll describe which layer, what it contains and what naming conventions are we using.
1) The Project
When you setup your BigQuery integration, you pick a project of your preference to store your data.
That's where all the data sources you connect are sent to:
2) The Dataset
A dataset is a collection of tables.
Each dataset equals one of the sources you connected under your Easy App Reports account (eg. Google Play, App Store, Meta Ads, etc).
Because your account can hold multiple sources, we had to give each dataset an unique name. We also had to make it readable as that's the name you'll see on Looker Studio or while if you're writing queries.
Here's the structure we're using:
ear[num]_[source]_[account_name]
Where:
account_name: your developer account name, truncated after 4 characters of each word (eg. "Meta Platform" becomes meta_plat);
source: the name of the source, such as appstore, googleplay, googleads, etc;
num: indicates the order in which you added this data source to your account.
Examples:
ear0_googleplay_meta_plat
ear1_appstore_meta_plat
ear2_metaads_meta_plat
3) The Tables
These follow the the same snake case model.
[abbreviated_source]_[table_name]
Examples:
gdc_installs: Google Developer Console - Installs
gdc_reviews: Google Developer Console - Reviews
apc_sales_trends: App Store Connect - Trends
apc_analytics_source: App Store Connect - Analytics per Source
And so on.
Notice that all table names are actually the report names as seen in this page.
If you found this useful you might want to have a look at our Data Freshness and How BigQuery works articles or this tutorial on how to migrate from Looker Studio to BigQuery data sources.
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