Brainforge Knowledge

CES_Events_vs_Registration_Data

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CES: Events Data vs Registration Data

Quick reference for the difference between ces_events_history (events data) and ces_20XX_registration (registration data) in RAW.ARCHIVE_DATA.

Registration data — ces_2023_registration … ces_2026_registration

What it is: One row per person’s registration to the CES show for a given year.

Grain: One row per attendee per year (show-level registration).

Typical use: “Who is registered for CES 2026?” — counts by registration type (Industry, Exhibitor Personnel, Media), geography, product category, demographics, on-site vs pre-show, and (when joined to badge scans) confirmed attendance.

Key fields (conceptually):

  • Identity: email, first_name, last_name, company
  • Show registration: ces_year, reg_type (ATT, EX, MEDIA, etc.), badgecount, cancel_flag
  • Geography: country, region
  • Demographics: primary_business, product_code/product_category, title_coded/job_function, buying_influence, customer_base, company_revenue_band
  • Timing: registration_week, reg_interface (e.g. on-site vs pre-show)
  • Ranking flags: fortune_500, interbrand, twice/twice_appliance

Where it’s used in this repo:

  • stg_member_engagement__ces_registration — unified staging of 2023–2026 registrations (identity + badgecount)
  • int_ces__registration_audit_wide — full audit model (reg type, geography, is_onsite, demographics, attended_flag via badge scans)
  • rpt_ces_attendance_registration_overview — reporting mart for CES registration/attendance Tasks 1–17

Source: Year-specific exports (e.g. CES_2026_REGISTRATION) loaded into RAW.ARCHIVE_DATA.

Events data — ces_events_history

What it is: One row per person’s relationship to a specific event or session (e.g. a conference session, keynote, or track). Includes both “registered” and “attended” for those events.

Grain: One row per person per event/session (multiple rows per person per year).

Typical use: “Who attended which sessions?” “Which events did this company’s people go to?” “Speaker attendance,” org-level event registration/attendance rollups.

Key fields (conceptually):

  • Identity: email_address, first_name, last_name, company, impex_org_id
  • Event/session: event_title, event_type, session_title, event_date, event_status
  • Registration to event: reg_type, reg_type_detail, registered_week, reg_days_difference
  • Status: event_status (e.g. 'attended', 'registered')
  • Other: speaker_flag, product_code, year, show_type, attribution, source_file_name

Where it’s used in this repo:

  • stg_member_engagement__events_attendance — rows where event_status = 'attended' (excludes speakers)
  • stg_member_engagement__events_speakers — rows where speaker_flag in (‘y’,‘yes’) and event_status = 'attended'
  • stg_member_engagement__events_reg_and_attendance — aggregated by impex_org_id, year, reg_type, event_status (for org-level engagement)

Source: Historical CES events/sessions data (attendance, registrations, speakers) in RAW.ARCHIVE_DATA.

Side-by-side

AspectRegistration data (ces_20XX_registration)Events data (ces_events_history)
GrainOne row per person per show yearOne row per person per event/session
Question“Who is registered for CES 2026?”“Who attended/registered for this session/event?”
Event/sessionNo event_title or session_titleevent_title, event_type, session_title
Statuscancel_flag (show registration)event_status (e.g. attended, registered for that event)
Use in this repoCES registration audit, attendance by type/geo/demographicsMember engagement: event attendance, speakers, org rollups

Relationship to badge scans

  • Registration data is joined to badge_scans (e.g. in int_ces__registration_audit_wide) to get show-level “confirmed attendance” (someone scanned in at the show). Badge_scans in this repo are 2026-only.
  • Events data already carries event-level attendance via event_status = 'attended' for specific sessions/events; it’s a different source from physical badge scans and is used for session/event analytics, not for the main “CES 2026 registration + show attendance” audit.

Summary: Use registration data for “who’s registered for the show and who showed up (badge scan)” and demographics. Use events data for “who attended or registered for which specific events/sessions” and engagement analytics.

Graph View