## DataMart: model open for customers usage
{}_{dimension}_{filtering}_{usecase_details}// filtering and usecase coule be skipped
### Names Examples:
Cubes:
— meta_ads_daily
- google_ads_daily
— google_ads_daily_campaigns
- all_ads_monthly_region_roas
— all_ads_daily // if we going to union all sources/channels
Entities:
- meta_ads_campaigns
— google_ad_sets
- google_ads_keywords
- meta_ads_creatives
- all_ads_channels
- countries
Events:
- ga4_events
- meta_ads_events_settings_changes
- shopify_events_sales_order_complited
— events_crm_order_cancelations
— events_airbyte_exttaction_log_status
## subject_domains
- ads platforms domains
— google_ads_
— meta_ads_
— pinterest_
- analytics tools
— ga4_
- amplitude_
our own domain
— all_ads_ // models that unite all ads platforms data together
customer data models
- by_vbb_
## Intermediate DataModel:
{intermediate}_{granularity_type}_{filtering}_{dimension}_{usecase}
### Names Examples:
- intermediate_daily_meta_ads_with_campaign_name_fixes
- intermediate_entity_creatives_with_accomulative_stats_materialized
## Source DataModel:
{source}_{granularity_type}_{filtering}_{dimension}_{usecase} // filtering and are not mundatory
### Names Examples:
- source_daily_meta_ads_with_campaign_name_fixes
- intermediate_entity_creatives_with_accomulative_stats_materialized
## metric layer on cubes
we use group by cube(dimensions) and add postfix _cube
kobzevvv / granula Goto Github PK
View Code? Open in Web Editor NEWdatasets modeling aproach with examples
License: MIT License