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            Bookings

            scheduleLast updated on November 13, 2026

            1. Dataset name

            Bookings - Resource Management

            2. Description

            Booking-level dataset that records each time an employee was booked onto a Resource Management demand. Each booking carries its dates, status, hours per day, and duration, along with the bench time (idle days) the employee had between their previously approved booking and this one. Demand attributes (title, status, location, program, project) are denormalized onto each booking. It is built from customer_views.employee_bookings, enriched with demand context from customer_views.positions. It is designed to be the primary source for booking volume, booking trend, and bench-time analyses.

            3. Source tables

            • customer_views.employee_bookings — demand bookings; the anchor of the dataset
            • customer_views.positions — demands, filtered to the resourcing system

            4. Grain

            One row per booking_id. Bookings are the LEFT JOIN anchor, so a booking whose demand is not an active resourcing demand still appears, with all demand-level fields (demand_title, demand_status, program_name, etc.) null. A demand with multiple bookings appears once per booking.

            5. Dashboards supported

            • Resource Management

            6. Metrics supported

            Metric Supported breakdowns
            Bookings Created —
            Booking Creation Trend —
            Bench Time —

            7. Known exclusions and filters applied

            • Archived bookings are excluded.
            • Demand context comes only from resourcing demands that have not been deleted.
            • Bookings of every status are included. Bench time, previous booking end date, and the first-booking markers are calculated from approved bookings only, so these fields are null (or 0 for is_demand_first_booking) on bookings with any other status.
            • Bench time is measured against the employee's most recent earlier approved booking. It is null on an employee's first approved booking, since there is no earlier booking to measure from.
            • A booking that starts before the employee's previous approved booking ends has negative bench days and falls in the Overlapping bucket.
            • is_active_today is based on booking dates only and applies to bookings of every status.
            • booking_duration_days counts both the start date and the end date.
            • The dataset logic applies no date filter; it covers all-time history.

            8. Schema

            Column name Data type Notes
            booking_id BIGINT Primary grain key for this dataset
            employee_id VARCHAR Employee who was booked
            demand_id BIGINT Demand the employee was booked onto; join key to customer_views.positions
            created_by VARCHAR User who created the booking
            created_at DATETIME Booking creation timestamp; basis for Bookings Created and Booking Creation Trend
            start_date DATETIME Date the booking starts
            end_date DATETIME Date the booking ends
            booking_status VARCHAR Status of the booking (e.g. approved)
            hours_per_day DOUBLE Hours per day the employee is booked for
            booking_duration_days BIGINT Derived: days from start_date to end_date, counting both the start and end dates
            prev_booking_end_date DATETIME Derived: end date of the employee's previous approved booking; populated for approved bookings only
            bench_days BIGINT Derived: idle days between the end of the employee's previous approved booking and the start of this one; 0 for back-to-back bookings; negative when the bookings overlap; powers Bench Time
            bench_days_bucket VARCHAR Derived bucket of bench_days: Overlapping (below 0), 0 day, A) 1–7, B) 8–30, C) 31–90, D) 90+ days
            is_active_today BIGINT Derived: 1 if today falls between start_date and end_date
            demand_title VARCHAR Title of the demand
            demand_status VARCHAR Status of the demand, from the demand's custom attributes
            demand_creation_ts DATETIME Demand creation timestamp
            demand_first_booking_ts DATETIME Derived: creation timestamp of the first approved booking on the demand
            is_demand_first_booking BIGINT Derived: 1 if this is the first approved booking created on the demand
            recruiter VARCHAR Recruiter on the demand, as stored on the demand record
            hiring_manager VARCHAR Hiring manager on the demand, as stored on the demand record
            demand_location_country VARCHAR Location country of the demand
            program_id VARCHAR ID of the program the demand belongs to
            program_name VARCHAR Name of the program the demand belongs to
            project_id VARCHAR ID of the project the demand belongs to
            project_name VARCHAR Name of the project the demand belongs to
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