Snowflake Object Inventory¶

Purpose: Complete map of every Snowflake database, schema, and table/view in production. Claude Code uses this to avoid naming conflicts and understand the current state of the warehouse.

Last Updated: 2026-05-25 Maintained by: Keep this current when adding new databases, schemas, or tables.

How to Update This File¶

When you create a new Snowflake object (via schemachange migration or dbt), add it here immediately. This prevents duplicate names, aids debugging, and gives Claude Code accurate context for every session.

Databases¶

Database	Client	Environment	Owner	Purpose
`WBP_DB`	Warby Parker	Production	XO_DATA_ENGINEER	Medallion layers: Bronze → Silver → Gold
`WBP_DB_DEV`	Warby Parker	Development	XO_DATA_ENGINEER	Dev/testing (mirrors WBP_DB structure)
`CND_DB`	Condé Nast	Production	XO_DATA_ENGINEER	Medallion layers: Bronze → Silver → Gold
`CND_DB_DEV`	Condé Nast	Development	XO_DATA_ENGINEER	Dev/testing
`JCR_DB`	J.Crew	Production	XO_DATA_ENGINEER	Medallion layers: Bronze → Silver → Gold
`JCR_DB_DEV`	J.Crew	Development	XO_DATA_ENGINEER	Dev/testing (mirrors JCR_DB structure)
`CORE_DB`	Shared	Production	XO_DATA_ENGINEER	Shared resources: employee rosters, shared dims
`CORE_DB_DEV`	Shared	Development	XO_DATA_ENGINEER	Dev/testing
`OPERATIONS`	Legacy	Production	XO_DATA_ENGINEER	Legacy reporting DB — being deprecated
`MAESTRO_DB`	Condé Nast (Rippit)	Production	MAESTRO_ROLE (Rippit team)	Partner-managed Bronze for CND QA evaluation data — see ADR 017

WBP_DB (Warby Parker)¶

BRONZE Schema¶

All Bronze tables: all VARCHAR columns, batch_replace loading strategy.

Table	Source System	Load Strategy	DAG	Schemachange Version
`GLADLY_CONTACT_TIMESTAMPS`	Gladly API	batch_replace	wbp_gladly_extract_daily	V1.1.0
`GLADLY_CONVERSATION_TIMESTAMPS`	Gladly API	batch_replace	wbp_gladly_extract_daily	V1.1.0
`GLADLY_WORK_SESSIONS`	Gladly API	batch_replace	wbp_gladly_extract_daily	V1.3.0
`GLADLY_AGENT_DURATIONS`	Gladly API	batch_replace	wbp_gladly_extract_daily	V1.4.0
`GLADLY_AGENT_SUMMARY`	Gladly API	batch_replace	wbp_gladly_extract_daily	—
`GSHEETS_CSAT`	Google Sheets	incremental	wbp_gsheets_extract_daily	V1.5.0
`GSHEETS_QA`	Google Sheets	incremental	wbp_gsheets_extract_daily	V1.5.0
`ASPECT_CONFORMANCE`	Aspen WFM (Google Drive)	batch_replace	wbp_aspect_gdrive_extract_weekly	V1.16.2
`AWS_QUEUE_PRODUCTIVITY`	AWS Connect (Google Drive)	append	wbp_aws_gdrive_extract_daily	V1.21.0
`AWS_AGENT_PERFORMANCE`	AWS Connect (Google Drive)	append	wbp_aws_gdrive_extract_daily	V1.22.0
`AWS_AGENT_PRODUCTIVITY`	AWS Connect (Google Drive)	append	wbp_aws_gdrive_extract_daily	V1.23.0
`AWS_CSAT`	AWS Connect (Google Drive)	append	wbp_aws_gdrive_extract_daily	V1.25.0

SILVER Schema¶

All Silver tables: dbt dynamic tables, typed columns, deduplicated by RECORD_KEY.

Table	Source Bronze Table	dbt Model	Grain
`CONTACT_TIMESTAMPS`	GLADLY_CONTACT_TIMESTAMPS	`silver/warbyparker/contact_timestamps.sql`	One row per CONTACT_ID
`CONVERSATION_TIMESTAMPS`	GLADLY_CONVERSATION_TIMESTAMPS	`silver/warbyparker/conversation_timestamps.sql`	One row per CONVERSATION_ID
`WORK_SESSIONS`	GLADLY_WORK_SESSIONS	`silver/warbyparker/work_sessions.sql`	One row per AGENT_ID + SESSION_START
`AGENT_DURATIONS`	GLADLY_AGENT_DURATIONS	`silver/warbyparker/agent_durations.sql`	One row per AGENT_ID + STATUS_START
`AGENT_SUMMARY`	GLADLY_AGENT_SUMMARY	`silver/warbyparker/wbp_gladly_agent_summary.sql`	One row per AGENT_ID + day
`INBOX_GLOSSARY`	External / Manual	N/A (managed separately)	One row per INBOX_ID
`WBP_ASPECT_CONFORMANCE`	ASPECT_CONFORMANCE	`warbyparker/silver/wbp_aspect_conformance.sql`	One row per (EID × date)
`WBP_AWS_CSAT`	AWS_CSAT	`warbyparker/silver/wbp_aws_csat.sql`	One row per (contact × question)

GOLD Schema¶

Object	Type	dbt Model	Source	Grain
`FCT_CONTACTS`	Dynamic Table	`gold/warbyparker/fct_contacts.sql`	SILVER.CONTACT_TIMESTAMPS + CORE_DB.SILVER.ROSTER_WARBYPARKER	One row per CONTACT_ID
`AGG_AGENT_DAILY_CONTACTS`	Dynamic Table	`gold/warbyparker/agg_agent_daily_contacts.sql`	FCT_CONTACTS	One row per (AGENT_ID, CONTACT_DATE)
`RPT_EMAIL_DAILY`	View	`gold/warbyparker/rpt_email_daily.sql`	AGG_AGENT_DAILY_CONTACTS	One row per (AGENT_ID, DATE)
`RPT_AI_VS_NONAI_QA_WOW`	View	`gold/warbyparker/rpt_ai_vs_nonai_qa_wow.sql`	fct_qa_internal, fct_qa_partner	One row per (WEEK_START_DATE × AGENT_GROUP × SCORE_TYPE)
`RPT_AI_VS_NONAI_QA_QOQ`	View	`gold/warbyparker/rpt_ai_vs_nonai_qa_qoq.sql`	fct_qa_internal, fct_qa_partner	One row per (QUARTER_START_DATE × AGENT_GROUP × SCORE_TYPE)
`FCT_WBP_ASPECT_CONFORMANCE`	Table	`warbyparker/gold/fct_wbp_aspect_conformance.sql`	WBP_ASPECT_CONFORMANCE + BI_ROSTER_WARBYPARKER	One row per (EID × date)
`FCT_WBP_AWS_CSAT`	Table	`warbyparker/gold/fct_wbp_aws_csat.sql`	WBP_AWS_CSAT + CORE_DB.SILVER.BI_ROSTER_WARBYPARKER	One row per contact (INITIAL_CONTACT_ID)
`AGG_WBP_AWS_CSAT_CHANNEL_DAILY`	Table	`warbyparker/gold/agg_wbp_aws_csat_channel_daily.sql`	FCT_WBP_AWS_CSAT	One row per (date × eid × interaction_type); SUM(stars) 1-5 + survey count; additive with AGG_WBP_CSAT_CHANNEL_DAILY in agent-performance view
`AI_AGENTS`	Seed Table	`seeds/ai_agents.csv`	Static CSV	One row per agent (AI wave enablement dates)
`RPT_WBP_CONTACT_VOLUME`	View	`warbyparker/gold/rpt_wbp_contact_volume.sql`	FCT_WBP_CONTACTS	One row per (date × channel × vendor × ai_status × ai_wave); inbound contacts; AI status = roster enrollment
`EXP_WBP_CONTACT_VOLUME_INBOX`	View	`warbyparker/gold/exp_wbp_contact_volume_inbox.sql`	FCT_WBP_CONTACTS	Same grain as RPT_WBP_CONTACT_VOLUME; AI status = inbox-based (IS_AI_QUEUE)
`EXP_WBP_CONTACT_VOLUME_AGENT`	View	`warbyparker/gold/exp_wbp_contact_volume_agent.sql`	AGG_WBP_AGENT_SUMMARY_CHANNEL_DAILY	Same grain; XO only; AI status = roster enrollment; queued=accepted; fulfilled_same_day=NULL

SANDBOX Schema¶

Ad-hoc and supplementary datasets for analyst use. No pipeline automation, no dbt models. Tables follow the {SOURCE}_{OBJECT}_{ISSUE_NUMBER} naming convention. See ADR 015.

Table	Source	Loaded By	Issue	Notes
(tables added as needed — each linked to a GitHub issue)

CND_DB (Condé Nast)¶

BRONZE Schema¶

Table	Source System	Load Strategy	DAG	Schemachange Version
`SPROUT_MESSAGES`	Sprout Social API	batch_replace	condenast_sprout_messages_bronze	V1.6.0
`CND_MEDALLIA_CSAT`	Medallia (Stella Connect) API	batch_replace	condenast_medallia_daily	V1.2.0
`GLADLY_CONTACT_EXPORT`	Gladly ContactExportReportV3 API	merge (ADR 024)	condenast_gladly_exports_daily	V1.8.0
`GLADLY_CONVERSATION_EXPORT`	Gladly ConversationExportReport API	merge (ADR 024)	condenast_gladly_exports_daily	V1.8.0

SILVER Schema¶

Table	Source	dbt Model	Grain
`CND_MAESTRO_ANSWERS`	MAESTRO_DB (direct)	`cnd_maestro_answers`	One row per ANSWER_ID
`CND_MAESTRO_TEMPLATES`	MAESTRO_DB (direct)	`cnd_maestro_templates`	One row per TEMPLATE_ID
`CND_MAESTRO_HELPDESK_ID_EMAIL`	MAESTRO_DB (direct)	`cnd_maestro_helpdesk_id_email`	One row per HELPDESK + HELPDESK_ID
`CND_GLADLY_CONTACT_TIMESTAMPS`	`GLADLY_CONTACT_TIMESTAMPS` Bronze	`cnd_gladly_contact_timestamps`	One row per contact event
`CND_GLADLY_CONVERSATION_TIMESTAMPS`	`GLADLY_CONVERSATION_TIMESTAMPS` Bronze	`cnd_gladly_conversation_timestamps`	One row per conversation event
`CND_GLADLY_WORK_SESSIONS`	`GLADLY_WORK_SESSIONS` Bronze	`cnd_gladly_work_sessions`	One row per WORK_SESSION_ID
`CND_GLADLY_AGENT_DURATIONS`	`GLADLY_AGENT_DURATIONS` Bronze	`cnd_gladly_agent_durations`	One row per agent status span
`CND_GLADLY_AGENT_SUMMARY`	`GLADLY_AGENT_SUMMARY` Bronze	`cnd_gladly_agent_summary`	One row per AGENT_ID + day
`CND_GLADLY_FCR_BY_AGENT`	`GLADLY_FCR_BY_AGENT` Bronze	`cnd_gladly_fcr_by_agent`	One row per agent + day
`CND_GLADLY_CONTACT_EXPORT`	`GLADLY_CONTACT_EXPORT` Bronze	`cnd_gladly_contact_export`	One row per CONTACT_ID (latest state)
`CND_GLADLY_CONVERSATION_EXPORT`	`GLADLY_CONVERSATION_EXPORT` Bronze	`cnd_gladly_conversation_export`	One row per CONVERSATION_ID (latest state)

GOLD Schema¶

Table / View	Type	dbt Model	Grain / Purpose
`FCT_CND_CONTACTS`	Table	`condenast/gold/fct_cnd_contacts`	One row per contact — master contact fact
`FCT_CND_CONVERSATIONS`	Table	`condenast/gold/fct_cnd_conversations`	One row per conversation
`FCT_CND_CONTACTS_EXPORT`	Table	`condenast/gold/fct_cnd_contacts_export`	One row per contact, from the Gladly ContactExportReportV3 rolling-window export
`FCT_CND_CONVERSATIONS_EXPORT`	Table	`condenast/gold/fct_cnd_conversations_export`	One row per conversation, from the Gladly ConversationExportReport rolling-window export
`FCT_CND_QA`	Table	`condenast/gold/fct_cnd_qa`	One row per QA evaluation (from MAESTRO_ANSWERS)
`FCT_CND_AGENT_DURATIONS`	Table	`condenast/gold/fct_cnd_agent_durations`	One row per agent status duration record (contiguous status block)
`FCT_CND_AGENT_SUMMARY_DAILY`	Table	`condenast/gold/fct_cnd_agent_summary_daily`	One row per agent per day
`FCT_CND_AGENT_CHANNEL_SUMMARY`	Table	`condenast/gold/fct_cnd_agent_channel_summary`	One row per agent per day per channel
`AGG_CND_AGENT_DURATIONS_DAILY`	Table	`condenast/gold/agg_cnd_agent_durations_daily`	One row per (date × EID)
`AGG_CND_AGENT_SUMMARY_CHANNEL_DAILY`	Table	`condenast/gold/agg_cnd_agent_summary_channel_daily`	One row per (date × EID × channel)
`AGG_CND_FCR_CHANNEL_DAILY`	Table	`condenast/gold/agg_cnd_fcr_channel_daily`	One row per (date × EID × channel)
`RPT_CND_AGENT_PERFORMANCE_CHANNEL`	View	`condenast/gold/rpt_cnd_agent_performance_channel`	One row per (date × EID × channel) — Tableau-ready
`RPT_CND_AGENT_PRODUCTIVITY_DAILY`	View	`condenast/gold/rpt_cnd_agent_productivity_daily`	One row per (date × EID); all XO agents, no AI filter

Pending (not yet built): AGG_CND_QA_DAILY and RPT_CND_QA_DAILY exist in condenast/gold/_pending/ and are excluded from the build. Move out of _pending/ and update this table when they are activated.

SANDBOX Schema¶

Ad-hoc and supplementary datasets for analyst use. No pipeline automation, no dbt models. Tables follow the {SOURCE}_{OBJECT}_{ISSUE_NUMBER} naming convention. See ADR 015.

Table	Source	Loaded By	Issue	Notes
(tables added as needed — each linked to a GitHub issue)

JCR_DB (J.Crew)¶

BRONZE Schema¶

Table	Source System	Load Strategy	DAG	Schemachange Version
`GDRIVE_JCREW_AAA`	Google Drive GSheets (AAA weekly export)	batch_replace	jcr_gdrive_extract_daily	V1.3.0
`GDRIVE_JCREW_INTERACTIONS`	Google Drive (Genesys Cloud conversation-level export, daily)	append	jcr_gdrive_extract_daily	V1.5.0
`GDRIVE_JCREW_CSAT`	Google Drive GSheets (CSAT weekly export)	batch_replace	jcr_gdrive_extract_daily	V1.2.1
`GDRIVE_JCREW_FCR`	Google Drive GSheets (FCR weekly export)	batch_replace	jcr_gdrive_extract_daily	V1.2.2
`GDRIVE_JCREW_QA`	Google Drive (Genesys Cloud interactions QA / evaluation export, weekly)	append	jcr_gdrive_extract_daily	V1.6.0
`GDRIVE_JCREW_AGENT_DAILY_AHT`	Google Drive (Genesys Cloud agent performance summary, daily export)	append	jcr_gdrive_extract_daily	V1.4.0
`GDRIVE_JCREW_AGENT_STATUS`	Google Drive (Genesys Cloud agent status/adherence summary, daily export)	append	jcr_gdrive_extract_daily	V1.7.0

SILVER Schema¶

Table	Source	dbt Model	Grain
`JCR_GDRIVE_AAA`	`GDRIVE_JCREW_AAA` Bronze	`jcrew/silver/jcr_gdrive_aaa`	One row per ASSOCIATE × date
`JCR_GDRIVE_INTERACTIONS`	`GDRIVE_JCREW_INTERACTIONS` Bronze	`jcrew/silver/jcr_gdrive_interactions`	One row per conversation
`JCR_GDRIVE_CSAT`	`GDRIVE_JCREW_CSAT` Bronze	`jcrew/silver/jcr_gdrive_csat`	One row per CSAT record
`JCR_GDRIVE_FCR`	`GDRIVE_JCREW_FCR` Bronze	`jcrew/silver/jcr_gdrive_fcr`	One row per agent × channel × contact reason × week
`JCR_GDRIVE_QA`	`GDRIVE_JCREW_QA` Bronze	`jcrew/silver/jcr_gdrive_qa`	One row per conversation
`JCR_GDRIVE_AGENT_DAILY_AHT`	`GDRIVE_JCREW_AGENT_DAILY_AHT` Bronze	`jcrew/silver/jcr_gdrive_agent_daily_aht`	One row per agent × interval × media type
`JCR_GDRIVE_AGENT_STATUS`	`GDRIVE_JCREW_AGENT_STATUS` Bronze	`jcrew/silver/jcr_gdrive_agent_status`	One row per agent × interval (daily); no channel

GOLD Schema¶

Table / View	Type	dbt Model	Grain / Purpose
`FCT_JCR_AAA`	Table	`jcrew/gold/fct_jcr_aaa`	One row per agent × date; enriched with `bi_roster_jcrew`
`FCT_JCR_CSAT`	Table	`jcrew/gold/fct_jcr_csat`	One row per CSAT record; enriched with `bi_roster_jcrew`
`FCT_JCR_FCR`	Table	`jcrew/gold/fct_jcr_fcr`	One row per agent × channel × contact reason × week; enriched with `bi_roster_jcrew`
`AGG_JCR_AAA_DAILY`	Table	`jcrew/gold/agg_jcr_aaa_daily`	(date, EID, site, skill) — AAA sums from `FCT_JCR_AAA`
`AGG_JCR_CSAT_CHANNEL_DAILY`	Table	`jcrew/gold/agg_jcr_csat_channel_daily`	(date, EID, site, channel) — CSAT sums from `FCT_JCR_CSAT`
`AGG_JCR_FCR_CHANNEL_WEEKLY`	Table	`jcrew/gold/agg_jcr_fcr_channel_weekly`	(week_date, EID, channel, site) — FCR sums from `FCT_JCR_FCR`
`AGG_JCR_AGENT_METRICS_DAILY`	Table	`jcrew/gold/agg_jcr_agent_metrics_daily`	(date, EID, site, channel, SOURCE) — compact wide; ~4 rows per agent × date (Phone, Email, Chat, ALL); CSAT survey cols merged onto Chat AAA row; FCR rows at weekly grain; combines AAA/CSAT/FCR aggs
`RPT_JCR_AGENT_PERFORMANCE`	View	`jcrew/gold/rpt_jcr_agent_performance`	(week_date, EID, channel, site) — weekly CSAT + FCR for Tableau
`FCT_JCR_AHT_OPS`	Table	`jcrew/gold/fct_jcr_aht_ops`	One row per agent × interval × media_type; AGENT_ID → `bi_roster_jcrew_new`.GENESYS_ID; XO + non-XO retained (spike #1269)
`AGG_JCR_AHT_CHANNEL_DAILY_OPS`	Table	`jcrew/gold/agg_jcr_aht_channel_daily_ops`	(date, agent_id, media_type) — AHT sums from `FCT_JCR_AHT_OPS`; XO + non-XO
`RPT_JCR_AHT_ACCOUNT_OPS`	View	`jcrew/gold/rpt_jcr_aht_account_ops`	(date, media_type, agent_group=XO/Non-XO) — account-level AHT for Tableau
`FCT_JCR_INTERACTIONS`	Table	`jcrew/gold/fct_jcr_interactions`	One row per conversation (last-agent-wins); last USERS_INTERACTED token → `bi_roster_jcrew_new`.USER_NAME; BPO_GROUP = XtendOps / J.Crew Corporate; non-XO retained (#1275/#1347)
`AGG_JCR_INTERACTIONS_CHANNEL_DAILY`	Table	`jcrew/gold/agg_jcr_interactions_channel_daily`	(date, media_type, BPO_GROUP) — conversation volume + duration sums from `FCT_JCR_INTERACTIONS`
`RPT_JCR_INTERACTIONS_VOLUME`	View	`jcrew/gold/rpt_jcr_interactions_volume`	(date, media_type, BPO_GROUP) — account conversation volume + AHT for Tableau
`EXP_JCR_INTERACTIONS_JOIN_COVERAGE`	View	`jcrew/gold/exp_jcr_interactions_join_coverage`	Coverage comparison: explode vs direct USER_NAME join (spike #1275)
`FCT_JCR_QA`	Table	`jcrew/gold/fct_jcr_qa`	One row per conversation (latest scored evaluation; all-Retracted/Deleted dropped); TRIM(EVALUATED_AGENT) → `bi_roster_jcrew_new`.USER_NAME; BPO_GROUP = XtendOps / J.Crew Corporate; non-XO retained (#1290/#1349)
`AGG_JCR_QA_CHANNEL_DAILY`	Table	`jcrew/gold/agg_jcr_qa_channel_daily`	(date, evaluated_agent, media_type) — QA score sums/counts from `FCT_JCR_QA`, carries BPO_GROUP; XO + non-XO
`RPT_JCR_QA_AGENT_SCORECARD`	View	`jcrew/gold/rpt_jcr_qa_agent_scorecard`	(date, evaluated_agent, media_type) — per-agent QA scorecard for Tableau, carries BPO_GROUP
`RPT_JCR_QA_ACCOUNT`	View	`jcrew/gold/rpt_jcr_qa_account`	(date, media_type, BPO_GROUP) — account-level QA for Tableau
`FCT_JCR_AGENT_DAILY_AHT`	Table	`jcrew/gold/fct_jcr_agent_daily_aht`	One row per AGENT_ID × interval × media_type; 3-key COALESCE → `bi_roster_jcrew_new`; BPO_GROUP = XtendOps / J.Crew In-House / J.Crew Corporate (#1343) ✅ Production
`AGG_JCR_AGENT_DAILY_AHT`	Table	`jcrew/gold/agg_jcr_agent_daily_aht`	(INTERVAL_DATE, AGENT_ID, MEDIA_TYPE) — HANDLE > 0; XO + non-XO retained, keyed on agent_id (#1343)
`RPT_JCR_HANDLE_TIME_DAILY`	View	`jcrew/gold/rpt_jcr_handle_time_daily`	(INTERVAL_DATE, AGENT_ID, MEDIA_TYPE) — per-agent AHT/handle-time KPIs, all BPO groups (#1343)
`FCT_JCR_AGENT_STATUS`	Table	`jcrew/gold/fct_jcr_agent_status`	One row per AGENT_ID × interval (daily), no channel; 3-key COALESCE → `bi_roster_jcrew_new`; BPO_GROUP = XtendOps / J.Crew Corporate (no site field, no In-House bucket) (#1322) 🟡 New
`AGG_JCR_AGENT_STATUS_DAILY`	Table	`jcrew/gold/agg_jcr_agent_status_daily`	(INTERVAL_DATE, AGENT_ID) — LOGGED_IN > 0; XO + non-XO retained, keyed on agent_id (#1322) 🟡 New
`RPT_JCR_AGENT_STATUS_DAILY`	View	`jcrew/gold/rpt_jcr_agent_status_daily`	(INTERVAL_DATE, AGENT_ID) — per-agent adherence/occupancy rates, all BPO groups (#1322) 🟡 New

SANDBOX Schema¶

Ad-hoc and supplementary datasets for analyst use. No pipeline automation, no dbt models. Tables follow the {SOURCE}_{OBJECT}_{ISSUE_NUMBER} naming convention. See ADR 015.

Table	Source	Loaded By	Issue	Notes
(tables added as needed — each linked to a GitHub issue)

CORE_DB (Shared Resources)¶

BRONZE Schema¶

All Bronze tables: all VARCHAR columns, batch_replace loading strategy (one row per employee per BATCH_ID).

PH HR Roster tables — source: Google Sheets (PeopleHub/BambooHR export):

Table	Source Sheet Tab	DAG	Schemachange Version
`PH_HR_ROSTER_ACTIVE`	PH HR Active	core_ph_hr_roster_daily	V1.33.0
`PH_HR_ROSTER_INACTIVE`	PH HR Inactive	core_ph_hr_roster_daily	V1.34.0

BI Roster tables — source: Standard_Roster Google Sheet (1TDfcwDHQFM3fmAJhQOzoWjDbTikJCN0wvQ5RYh2xjNY), all loaded by core_gsheets_bi_roster_daily DAG:

Table	Sheet Tab	Schemachange Version
`GSHEET_BI_ROSTER_WARBYPARKER`	WARBYPARKER	V1.5.1
`GSHEET_BI_ROSTER_BI_TEAM`	Bi Team	V1.6.0
`GSHEET_BI_ROSTER_STAFF_MX`	STAFF MX	V1.7.0
`GSHEET_BI_ROSTER_MORGANANDMORGAN`	MORGANANDMORGAN	V1.8.0
`GSHEET_BI_ROSTER_QUADLOCK`	QUADLOCK	V1.9.0
`GSHEET_BI_ROSTER_IONOS`	IONOS	V1.10.0
`GSHEET_BI_ROSTER_FLARE`	FLARE	V1.11.0
`GSHEET_BI_ROSTER_POSTMAN_LAW`	POSTMAN LAW	V1.12.0
`GSHEET_BI_ROSTER_RUGIET`	RUGIET	V1.13.0
`GSHEET_BI_ROSTER_JCREW`	JCREW	V1.14.0
`GSHEET_BI_ROSTER_JCREW_NEW`	JCREW_NEW	V1.37.0
`GSHEET_BI_ROSTER_KELLER_POSTMAN`	KELLER POSTMAN	V1.15.0
`GSHEET_BI_ROSTER_CONDENAST`	CONDENAST	V1.16.0
`GSHEET_BI_ROSTER_WITHIN_HEALTH`	WITHIN HEALTH	V1.17.0
`GSHEET_BI_ROSTER_WESTERN_DENTAL`	WESTERN DENTAL	V1.18.0
`GSHEET_BI_ROSTER_MATCH`	MATCH	V1.19.0
`GSHEET_BI_ROSTER_LOGITECH`	LOGITECH	V1.20.0
`GSHEET_BI_ROSTER_DRFIRST`	DRFIRST	V1.21.0
`GSHEET_BI_ROSTER_GOODFOOD`	GOODFOOD	V1.22.0
`GSHEET_BI_ROSTER_IMAGINE_WELLNESS`	IMAGINE WELLNESS	V1.23.0
`GSHEET_BI_ROSTER_NBA`	NBA	V1.24.0
`GSHEET_BI_ROSTER_TRIM`	TRIM	V1.25.0
`GSHEET_BI_ROSTER_UR_LABS`	UR LABS	V1.26.0
`GSHEET_BI_ROSTER_FLEX_MG`	FLEX MG	V1.27.0
`GSHEET_BI_ROSTER_CARTAMUNDI`	CARTAMUNDI	V1.28.0
`GSHEET_BI_ROSTER_HELLOFRESH`	HELLOFRESH	V1.29.0
`GSHEET_BI_ROSTER_HELLOFRESH_TERMS`	HELLOFRESH TERMS	V1.30.0
`GSHEET_BI_ROSTER_SMASHTECH`	SMASHTECH	V1.31.0

SILVER Schema¶

Shared resources used by all client Gold layers.

PH HR Roster — sourced from BRONZE.PH_HR_ROSTER_*:

Table	Purpose	dbt Model	Updated By
`PH_HR_ROSTER_ACTIVE`	PH active employee roster	`silver/core/ph_hr_roster_active.sql`	core_dbt_bi_roster DAG
`PH_HR_ROSTER_INACTIVE`	PH inactive employee roster	`silver/core/ph_hr_roster_inactive.sql`	core_dbt_bi_roster DAG

BI Rosters — sourced from BRONZE.GSHEET_BI_ROSTER_*, rebuilt each run from the latest BATCH_ID. One row per employee (current state):

Table	dbt Model	Client
`BI_ROSTER_WARBYPARKER`	`silver/core/bi_roster_warbyparker.sql`	Warby Parker
`BI_ROSTER_BI_TEAM`	`silver/core/bi_roster_bi_team.sql`	BI Team (internal)
`BI_ROSTER_STAFF_MX`	`silver/core/bi_roster_staff_mx.sql`	Staff MX
`BI_ROSTER_MORGANANDMORGAN`	`silver/core/bi_roster_morganandmorgan.sql`	Morgan & Morgan
`BI_ROSTER_QUADLOCK`	`silver/core/bi_roster_quadlock.sql`	Quad Lock
`BI_ROSTER_IONOS`	`silver/core/bi_roster_ionos.sql`	IONOS
`BI_ROSTER_FLARE`	`silver/core/bi_roster_flare.sql`	Flare
`BI_ROSTER_POSTMAN_LAW`	`silver/core/bi_roster_postman_law.sql`	Postman Law
`BI_ROSTER_RUGIET`	`silver/core/bi_roster_rugiet.sql`	Rugiet
`BI_ROSTER_JCREW`	`silver/core/bi_roster_jcrew.sql`	J.Crew
`BI_ROSTER_KELLER_POSTMAN`	`silver/core/bi_roster_keller_postman.sql`	Keller Postman
`BI_ROSTER_CONDENAST`	`silver/core/bi_roster_condenast.sql`	Condé Nast
`BI_ROSTER_WITHIN_HEALTH`	`silver/core/bi_roster_within_health.sql`	Within Health
`BI_ROSTER_WESTERN_DENTAL`	`silver/core/bi_roster_western_dental.sql`	Western Dental
`BI_ROSTER_MATCH`	`silver/core/bi_roster_match.sql`	Match
`BI_ROSTER_LOGITECH`	`silver/core/bi_roster_logitech.sql`	Logitech
`BI_ROSTER_DRFIRST`	`silver/core/bi_roster_drfirst.sql`	DrFirst
`BI_ROSTER_GOODFOOD`	`silver/core/bi_roster_goodfood.sql`	GoodFood
`BI_ROSTER_IMAGINE_WELLNESS`	`silver/core/bi_roster_imagine_wellness.sql`	Imagine Wellness
`BI_ROSTER_NBA`	`silver/core/bi_roster_nba.sql`	NBA
`BI_ROSTER_TRIM`	`silver/core/bi_roster_trim.sql`	Trim
`BI_ROSTER_UR_LABS`	`silver/core/bi_roster_ur_labs.sql`	UR Labs
`BI_ROSTER_FLEX_MG`	`silver/core/bi_roster_flex_mg.sql`	Flex MG
`BI_ROSTER_CARTAMUNDI`	`silver/core/bi_roster_cartamundi.sql`	Cartamundi
`BI_ROSTER_HELLOFRESH`	`silver/core/bi_roster_hellofresh.sql`	HelloFresh
`BI_ROSTER_SMASHTECH`	`silver/core/bi_roster_smashtech.sql`	Smashtech

GSHEET_BI_ROSTER_HELLOFRESH_TERMS has a Bronze table but no Silver model (terms-only reference data, not an employee roster).

Legacy rosters (deprecated — sourced from OPERATIONS.BAMBOOHR):

Table	Purpose	Updated By	Notes
`ROSTER_WARBYPARKER`	WBP XO agent roster (legacy)	core_ph_hr_roster_daily DAG	Being replaced by `DIM_EMPLOYEE_WARBYPARKER` in GOLD
`ROSTER_CONDENAST`	CND XO agent roster (legacy)	core_ph_hr_roster_daily DAG	Being replaced by `DIM_EMPLOYEE_CONDENAST` in GOLD

GOLD Schema¶

Employee dimensions for all clients (SCD Type 1 — latest state wins). Per ADR 010, all employee dimensions live here regardless of client.

Table	dbt Model	Source Silver	Client
`DIM_EMPLOYEE_WARBYPARKER`	`gold/core/dim_employee_warbyparker.sql`	`BI_ROSTER_WARBYPARKER`	Warby Parker
`DIM_EMPLOYEE_BI_TEAM`	`gold/core/dim_employee_bi_team.sql`	`BI_ROSTER_BI_TEAM`	BI Team
`DIM_EMPLOYEE_STAFF_MX`	`gold/core/dim_employee_staff_mx.sql`	`BI_ROSTER_STAFF_MX`	Staff MX
`DIM_EMPLOYEE_MORGANANDMORGAN`	`gold/core/dim_employee_morganandmorgan.sql`	`BI_ROSTER_MORGANANDMORGAN`	Morgan & Morgan
`DIM_EMPLOYEE_QUADLOCK`	`gold/core/dim_employee_quadlock.sql`	`BI_ROSTER_QUADLOCK`	Quad Lock
`DIM_EMPLOYEE_IONOS`	`gold/core/dim_employee_ionos.sql`	`BI_ROSTER_IONOS`	IONOS
`DIM_EMPLOYEE_FLARE`	`gold/core/dim_employee_flare.sql`	`BI_ROSTER_FLARE`	Flare
`DIM_EMPLOYEE_POSTMAN_LAW`	`gold/core/dim_employee_postman_law.sql`	`BI_ROSTER_POSTMAN_LAW`	Postman Law
`DIM_EMPLOYEE_RUGIET`	`gold/core/dim_employee_rugiet.sql`	`BI_ROSTER_RUGIET`	Rugiet
`DIM_EMPLOYEE_JCREW`	`gold/core/dim_employee_jcrew.sql`	`BI_ROSTER_JCREW`	J.Crew
`DIM_EMPLOYEE_KELLER_POSTMAN`	`gold/core/dim_employee_keller_postman.sql`	`BI_ROSTER_KELLER_POSTMAN`	Keller Postman
`DIM_EMPLOYEE_CONDENAST`	`gold/core/dim_employee_condenast.sql`	`BI_ROSTER_CONDENAST`	Condé Nast
`DIM_EMPLOYEE_WITHIN_HEALTH`	`gold/core/dim_employee_within_health.sql`	`BI_ROSTER_WITHIN_HEALTH`	Within Health
`DIM_EMPLOYEE_WESTERN_DENTAL`	`gold/core/dim_employee_western_dental.sql`	`BI_ROSTER_WESTERN_DENTAL`	Western Dental
`DIM_EMPLOYEE_MATCH`	`gold/core/dim_employee_match.sql`	`BI_ROSTER_MATCH`	Match
`DIM_EMPLOYEE_LOGITECH`	`gold/core/dim_employee_logitech.sql`	`BI_ROSTER_LOGITECH`	Logitech
`DIM_EMPLOYEE_DRFIRST`	`gold/core/dim_employee_drfirst.sql`	`BI_ROSTER_DRFIRST`	DrFirst
`DIM_EMPLOYEE_GOODFOOD`	`gold/core/dim_employee_goodfood.sql`	`BI_ROSTER_GOODFOOD`	GoodFood
`DIM_EMPLOYEE_IMAGINE_WELLNESS`	`gold/core/dim_employee_imagine_wellness.sql`	`BI_ROSTER_IMAGINE_WELLNESS`	Imagine Wellness
`DIM_EMPLOYEE_NBA`	`gold/core/dim_employee_nba.sql`	`BI_ROSTER_NBA`	NBA
`DIM_EMPLOYEE_TRIM`	`gold/core/dim_employee_trim.sql`	`BI_ROSTER_TRIM`	Trim
`DIM_EMPLOYEE_UR_LABS`	`gold/core/dim_employee_ur_labs.sql`	`BI_ROSTER_UR_LABS`	UR Labs
`DIM_EMPLOYEE_FLEX_MG`	`gold/core/dim_employee_flex_mg.sql`	`BI_ROSTER_FLEX_MG`	Flex MG
`DIM_EMPLOYEE_CARTAMUNDI`	`gold/core/dim_employee_cartamundi.sql`	`BI_ROSTER_CARTAMUNDI`	Cartamundi
`DIM_EMPLOYEE_HELLOFRESH`	`gold/core/dim_employee_hellofresh.sql`	`BI_ROSTER_HELLOFRESH`	HelloFresh
`DIM_EMPLOYEE_SMASHTECH`	`gold/core/dim_employee_smashtech.sql`	`BI_ROSTER_SMASHTECH`	Smashtech
`DIM_EMPLOYEE_PH`	`gold/core/dim_employee_ph.sql`	`PH_HR_ROSTER_ACTIVE`	PH (internal)

SANDBOX Schema¶

Ad-hoc and supplementary datasets for analyst use. No pipeline automation, no dbt models. Tables follow the {SOURCE}_{OBJECT}_{ISSUE_NUMBER} naming convention. See ADR 015.

Table	Source	Loaded By	Issue	Notes
(tables added as needed — each linked to a GitHub issue)

MAESTRO_DB (Rippit — Partner-Managed Bronze, Condé Nast)¶

Owner: Rippit team (MAESTRO_USER / MAESTRO_ROLE / RIPPIT_LOAD_WH) Pattern: Partner-managed Bronze — Rippit loads QA evaluation data directly; XO-Data reads cross-database from Silver models. See ADR 017.

MAESTRO Schema¶

Table	Source System	Owner	Notes
(tables loaded by Rippit team — explore via `DESCRIBE SCHEMA MAESTRO_DB.MAESTRO`)	Rippit QA	Rippit team	All read-only from XO-Data perspective

OPERATIONS (Legacy — Multi-Client Analytics DB)¶

This database contains legacy multi-client analytics objects. Actively maintained for ad hoc analysis and reporting; no _DEV variant exists — all queries run against prod data.

Schema	Objects	Purpose	Naming pattern
`STAGING`	~9 dynamic tables	Intermediate transformation layer	`STAGE_{CLIENT}_{OBJECT}`
`ODS`	~15 dynamic tables	Cross-client operational data store	`XOS_`, `{CLIENT}_`
`AGGREGATE`	~45 dynamic tables + ~36 views	Pre-computed metrics and dashboards	`{CLIENT}_{METRIC}`, `{CLIENT}_RPT_*`
`BAMBOOHR`	~7 dynamic tables	Employee roster source (feeds CORE_DB)	`ROSTER_{CLIENT}`

Do not create new objects in OPERATIONS. For new analytical surfaces, build in the medallion architecture (WBP_DB/CND_DB GOLD layer). Existing objects are read-only for analysis.

Airflow Connections → Snowflake Mapping¶

Airflow Connection ID	Snowflake Database	Role	Used By
`snowflake_loader_prod`	WBP_DB, CND_DB, CORE_DB	XO_DATA_LOADER	xo-foundry load tasks
`snowflake_dbt_prod`	WBP_DB, CND_DB, CORE_DB	XO_DBT_ROLE	dbt transformations (via Cosmos)
`snowflake_loader_dev`	WBP_DB_DEV, CND_DB_DEV	XO_DATA_ENGINEER_DEV	Local development

Naming Constraints¶

Before creating any new Snowflake object, verify: 1. Table name doesn't already exist in this inventory 2. Follows naming convention from ADR 009 3. Lives in the correct database — per-client data in client DB, shared data in CORE_DB 4. Schemachange migration file created — DDL must go through version control