BRIGHT Datasets and Data Points

Available Datasets

FL3XX BRIGHT currently contains 21 datasets, encapsulating essential aspects of your operations. Each dataset provides insights tailored to specific operational segments — from financial data and crew dynamics to maintenance schedules and passenger manifests. Whether you are building custom dashboards in QuickSight or querying raw data via the FL3XX Data Lake, this reference covers what is in each dataset and how it can support your analysis.

1. Booking
2. Flight
3. Services
4. Maintenance
5. Crew
6. Timeline location
7. Expenses
8. Legs
9. Airports
10. Aircrafts
11. Staff
12. Persons
13. AOC
14. Accounts
15. Qualifications
16. Passengers
17. Maintenance Events
18. Aircraft Availability
19. Fees
20. Duties
21. Aircraft Activity

 

Data Refresh Schedule

BRIGHT refreshes its data three times a day, ensuring users have access to up-to-date information approximately every eight hours.

US Region (us-east-1.quicksight): 06:00, 14:00, and 22:00 UTC

EU Region (eu-central-1.quicksight): 03:00, 11:00, and 19:00 UTC

The Airports dataset follows a separate schedule and is refreshed weekly, every Sunday.

 

Data Inventory

BRIGHT currently covers approximately 1,200 data points across EU and US instances. For a comprehensive overview of all available data fields, please refer to the centralized Data Inventory Google Sheet. Every field in FL3XX is available for BRIGHT users to combine in dashboards as needed.

Operators with in-house data analysts who need access to raw data can connect to the FL3XX Data Lake, which provides direct access to all BRIGHT datasets via S3-compatible exports.

 

Dataset Descriptions

Booking

The Booking dataset offers comprehensive details regarding flight bookings, covering a wide range of information related to bookings and flights. This includes financial data, passenger information, itineraries, and booking status. Each row in the dataset represents a distinct booking, with each column portraying a different aspect of that booking.

The dataset also includes fields for actual and estimated flight and block times, covering various scenarios: Block Time (Act/Est) for ground time before departure and after arrival, Flight Time (Act/Est) for airborne durations, and separate fields for passenger (Pax) and positioning (Pos) legs. Data is sourced from the back-end flight table and excludes cancelled flights.

Benefits

1. Financial Forecasting: Adjust pricing strategies for maximum profitability by analysing quoted vs. sold amounts per booking.
2. Fleet Management: Optimise aircraft usage and reduce unnecessary maintenance costs through booking-level utilisation data.
3. Customer Analysis: Identify booking trends, enhance route offerings, and boost bookings with passenger and account insights.

Key Features

1. Financial Visibility: Includes pricing fields such as quoted and sold amounts, invoice totals, and fee breakdowns for each booking.
2. Block & Flight Time (Act/Est): Provides actual and estimated block and flight times, split between passenger (Pax) and positioning (Pos) legs.
3. Booking Status & Workflow: Tracks booking type, workflow state, and status. Cancelled flights are excluded from this dataset by default.
4. Passenger & Itinerary Details: Captures route information, passenger count, associated aircraft, and account details for each booking.
5. Flight Data Source: Sourced from the back-end flight table, enabling cross-reference with the Flight and Legs datasets.

Flight

The Flight dataset provides a comprehensive overview of flights, encompassing crucial details such as departure and arrival times and flight status. It includes a wide range of information: airport and fuel details, crew and passenger information, aircraft specifics, and additional insights such as cargo details and reasons for delays. Each row represents a unique flight.

Benefits

1. Operational Analysis: Minimise downtime and optimise schedules using detailed flight timing and status data.
2. Fuel Management: Ensure economical flight operations by tracking fuel uplifts and consumption per flight.
3. Operational KPIs: Identify trends and peak periods across flights to support forecasting and future planning.

Key Features

1. Flight Status & Timing: Tracks departure and arrival times (planned and actual), including on-block, off-block, takeoff, and landing timestamps.
2. Airport Details: ICAO and IATA codes for departure and arrival airports, alongside relevant operational context.
3. Cargo & Delay Data: Captures cargo weight and delay reasons to support operational analysis and on-time performance reporting.

Services

The Services dataset offers detailed information on various services associated with each flight, providing insights into hotel accommodations, handling, customs, migration, PPR/Slot arrangements, and permits. Each row represents a specific service linked to a flight, including the flight ID, service type, status, responsible party details, and timing information.

Benefits

1. Consumption Patterns: Analyse service usage across flights to secure cost-effective vendor contracts.
2. Customer Experience: Tailor services per route and passenger preferences using service-level detail.
3. Permissions Management: Minimise operational delays by tracking permit and slot statuses in real time.

Key Features

1. Service Type Classification: Covers hotel accommodations, handling, customs, migration, PPR/Slot arrangements, and permits — one row per service per flight.
2. Service Status Tracking: Monitors the current status of each service entry, enabling identification of pending vs. confirmed arrangements.
3. Responsible Party Details: Includes vendor, handler, and responsible party information for each service entry.
4. Flight Linkage: Each service row is linked to a specific flight ID, enabling drill-down analysis by flight or route.
   
   

Maintenance

The Maintenance dataset provides detailed insights into aircraft maintenance tasks, timelines, and associated details drawn from the FL3XX Timeline. Each entry represents a specific maintenance task, with columns covering task type, costs, status, and duration.

Benefits

1. Scheduling: Keep aircraft flight-ready by efficiently planning and tracking all scheduled maintenance tasks.
2. Financial Planning: Balance estimated and actual maintenance costs for accurate budget management.
3. Service Evaluation: Analyze provider performance and select the best maintenance partners using cost and quality data.

Key Features

1. Task Type & Status: Covers all maintenance tasks in the FL3XX Timeline, including task type, current status, and duration.
2. Cost Tracking: Includes both estimated and actual maintenance costs, enabling budget vs. actuals reporting across tasks and aircraft.
3. Timeline Integration: Start and end dates for each task support scheduling analysis and aircraft capacity planning.
4. Service Provider Details: Captures information on the providers and vendors associated with each maintenance task.

Crew

The Crew dataset provides valuable insights into roster entries, including duty types, number of movements, and locations sourced from the FL3XX roster page. Each row represents a unique roster entry.

To enhance crew activity reporting, the dataset incorporates flight assignment data, enabling reports that combine roster activities with flight records. Calculated fields combine crew duty start and end dates with flight movement times to support flexible reporting across different time references.

Pilot Flight Hours — Important Note:

In FL3XX, pilot flight hours are calculated using two main metrics: All Aircraft (Logged) and Block Time Actual. Logged hours begin from a specific 'as of' date set by the operator and include only 'auto' and 'manual' flight types after this date. Block Time Actual includes all valid flights regardless of the 'as of' date. To compare the two values accurately, always review the pilot's configured 'as of' date. If flight recency requires a Type Rating (TR), the calculation will only consider the TR's start date.

Benefits

1. Duty Management: Streamline rosters and reduce overtime through data-driven scheduling and duty period analysis.
2. Training Analysis: Ensure effective crew training by tracking duty types, frequencies, and training assignments.
3. Location Tracking: Efficiently position crew and ensure safety through location visibility across duty periods.

Key Features

1. Duty Type Classification: Each row represents a unique roster entry, classified by duty type (flight, standby, training, etc.) with start/end times and location.
2. Flight Assignment Integration: Combines crew roster data with flight assignment records for combined crew activity and flight reporting.
3. Pilot Flight Hours: Two metrics are available: All Aircraft (Logged), calculated from an operator-defined 'as of' date, and Block Time Actual, covering all valid flights regardless of that date.
4. Check-In & Check-Out Times: Includes check-in and check-out timestamps per crew role per flight (Captain, Co-Pilot, Flight Attendant), supporting duty compliance reporting.
5. Calculated Time Fields: Combines crew duty dates with flight movement times for flexible cross-reference and aggregate reporting.

 

 

Timeline Location

The Timeline Location dataset enables users to determine how long and how often each aircraft remains at specific locations. Flight records are grouped by aircraft ID and ordered chronologically by take-off time. The landing ICAO code from one record is matched with the take-off ICAO code of the subsequent record, and the duration between them — the ground time — is calculated in hours.

Benefits

1. Ground Time Analysis: Understand how long aircraft spend at each location to optimise turnaround planning and resource allocation.
2. Location Utilisation: Identify high-frequency locations and anticipate handling and resource needs before they become constraints.
3. Operational Continuity: Maintain a sequential, gap-free view of aircraft movements across your entire operation.

Key Features

1. Aircraft-Location Grouping: Records are grouped by aircraft ID and ordered chronologically by take-off time for sequential analysis.
2. Ground Time Calculation: Calculates the time interval between the landing of one flight and the take-off of the next, in hours, reflecting real operational ground time.
3. Sequential Record Linking: The landing ICAO code from each record is matched to the take-off ICAO code of the next, ensuring continuity across the aircraft's movement history.
4. Estimated and Actual Times: Includes both estimated and actual ground time fields for planned vs. actuals comparison.

Expenses

The Expenses dataset in BRIGHT provides detailed insights into expenses associated with bookings, flights, timeline tasks, and roster entries. Each entry represents a unique expense record, enabling thorough financial analysis across all major operational segments.

Benefits

1. Cost Control: Identify spending patterns across bookings, flights, and maintenance to support budget decisions and cost reduction.
2. Operational Reconciliation: Cross-reference expenses with bookings and flight records to verify correct cost attribution.
3. Vendor Management: Analyse expense categories and amounts by service provider to support contract negotiations and procurement decisions.

Key Features

1. Broad Coverage: Captures expenses linked to bookings, flights, timeline/maintenance tasks, and roster entries — one row per unique expense record.
2. Expense Categorisation: Includes expense type, amount, and currency for each record.
3. Operational Linkage: Links each expense to the relevant flight, booking, or timeline task via shared identifiers, enabling holistic cost analysis.

 

Legs

The Legs dataset provides a comprehensive overview of individual flight segments, detailing departure and arrival times, status, and other operational details. Each row represents a distinct flight segment, offering granular visibility into flight operations at a level below the Booking and Flight datasets.

Benefits

1. Leg-Level Analysis: Break down complex multi-leg trips into individual segments for granular operational and financial reporting.
2. Status Tracking: Monitor leg status — including cancellations — across the full booking lifecycle.
3. Route Planning Insight: Analyse departure and arrival patterns at the leg level for network and scheduling optimisation.

Key Features

1. Leg Granularity: Each row represents a distinct flight segment, enabling analysis at a finer level than the Flight or Booking datasets.
2. Departure & Arrival Times: Includes planned and actual departure and arrival timestamps per leg.
3. Flight Log Status: Captures the log status per leg (e.g., OK, OK Revised), supporting identification of closed vs. open legs.
4. Booking Linkage: Each leg is linked to its parent booking, enabling roll-up analysis across booking and leg levels.
5. Workflow & Status Fields: Includes workflow state and status fields, enabling accurate replication of confirmed, flown, and closed leg logic for downstream reporting.

 

Airports

 

The Airport dataset offers in-depth information about airports, enriching reporting capabilities for flight operations and planning. It includes details on airport locations, runway specifications, and operational statistics — providing a comprehensive reference for flight-related analysis.

Benefits

1. Runway Capacity Planning: Use detailed runway data to minimise delays and optimise operations by understanding airport capacity constraints.
2. Route Analysis: Enrich flight and leg reports with airport-specific geographic and operational context for more meaningful analysis.
3. Operational Benchmarking: Understand airport-level capabilities when planning fleet deployment and route decisions.

Key Features

1. Airport Identification: Includes ICAO and IATA codes, airport name, city, and country for comprehensive lookup and cross-referencing.
2. Location Data: Provides geographic coordinates (latitude/longitude) and timezone information for each airport.
3. Runway Specifications: Includes runway length and surface type data for capacity and operational planning.
4. Weekly Refresh: The airports dataset is updated every Sunday — separate from the standard BRIGHT data refresh cycle.

 

Aircrafts

The Aircraft dataset provides a wealth of information on aircraft in your FL3XX instance, enriching reporting capabilities for fleet management and flight operations. It includes details on aircraft type, maximum passenger capacity, owner, manager, and more.

Benefits

1. Fleet Management: Maintain an up-to-date view of all aircraft attributes to support deployment, scheduling, and capacity decisions.
2. Aircraft Type Optimisation: Analyse aircraft attributes to deploy the most suitable aircraft for each route, maximising efficiency and profitability.
3. Ownership Reporting: Track ownership and management details for each aircraft for administrative and contractual clarity.

Key Features

1. Aircraft Attributes: Includes aircraft type, type rating, category, and maximum passenger capacity.
2. Ownership & Management: Captures owner and manager details per aircraft for administrative and contractual reporting.

Unique Identifiers: Each aircraft is identified by Aircraft ID and tail number, enabling direct linkage to the Flight, Maintenance, Crew, and Duties datasets.

 

Staff

The Staff dataset provides extensive user-related information within FL3XX, including user roles, assignments, and flight hour logs. It covers user profiles with fields such as User ID, Full Name, User Status, Job Title, Role List, aircraft assignments, qualifications, and various logged flight hours.

Pilot flight hours are calculated through the All Aircraft (Logged) metric, reflecting total logged hours from a specific 'as of' date defined by the operator on the Staff page. Flights prior to this date are excluded. Only 'auto' and 'manual' flight types contribute to the total, providing an accurate representation of a pilot's experience within the defined timeframe while allowing for initial hours set by the operator to account for flight time not recorded in FL3XX.

Benefits

1. User Management: Manage user roles, statuses, and assignments to ensure optimal resource allocation and regulatory compliance.
2. Flight Hours Analysis: Track and analyse detailed flight hours logged by pilots to assess experience levels and support safety and training programs.
3. Resource Optimisation: Use assignment and role data to optimise crew and aircraft usage, enhancing overall operational efficiency.
4. Regulatory Compliance: Maintain accurate records of pilot hours and qualifications to meet aviation industry regulations and standards.

Key Features

1. User Profiles: Includes User ID, full name, status, job title, and role list for every user in the FL3XX instance.
2. Aircraft Assignments: Captures each user's assigned aircraft, enabling cross-reference with fleet and scheduling datasets.
3. Logged Flight Hours: Provides All Aircraft (Logged) hours, calculated from an operator-defined 'as of' date using only 'auto' and 'manual' flight types.
4. Qualifications Summary: Includes qualification data at the user level for a consolidated staff compliance view.

Persons

The Persons dataset provides comprehensive information about contacts and individuals in your FL3XX instance. It includes personal details such as roles, contact information, documents, personal characteristics, and vaccination records. The dataset supports multiple entries per user for contacts, documents, and vaccinations, ensuring a thorough profile for each individual.

Benefits

1. Detailed User Profiles: Generate comprehensive reports containing personal and professional information for each individual, including roles, accounts, and notes.
2. Regulatory Compliance: Monitor documents, vaccinations, and contacts based on user roles to ensure adherence to regulatory and safety requirements.
3. Customer Insights: Evaluate passenger records and preferences to enhance customer relationship management processes.

Key Features

1. Personal Details: Includes name, date of birth, gender, nationality, and contact information for each individual.
2. Document Records: Captures passport, visa, and other travel document details, with support for multiple documents per person.
3. Vaccination Records: Tracks vaccination data, supporting health compliance requirements for crew and passengers.
4. Multi-Entry Support: Accommodates multiple contacts, documents, and vaccination records per user to ensure a complete and accurate profile.

 

AOC

The AOC dataset provides detailed information on air operator certificates, supporting regulatory compliance and operational planning. Key fields include AOC ID, operator name, AOC number, issue date, expiration date, and associated aircraft and personnel. Multiple entries for persons and aircraft are consolidated into comma-separated values for clarity and accessibility.

Benefits

1. Regulatory Compliance: Ensure all AOC-related data is accurate and up to date to meet regulatory requirements.
2. Data Consolidation: Consolidate multiple entries for persons and aircraft into easily readable records, improving clarity and accessibility.
3. Efficient Management: Track AOC validity dates and operational restrictions to avoid certification lapses and ensure continuous compliance.

Key Features

1. AOC Identification: Includes AOC ID, operator name, AOC number, and issue and expiration dates for each certificate.
2. Aircraft & Personnel Associations: Links each AOC to its associated aircraft and personnel, consolidated as comma-separated values for easy reading.

 

Accounts

The Accounts dataset in BRIGHT is a robust collection of data on FL3XX accounts, capturing everything from account identities and billing information to associated personnel and preferences. Key fields include Account ID, Account Name, Contact Information, Account Status, Payment Conditions, Sales Information, and financial details such as invoices issued and total amount paid. The dataset supports multiple contacts and addresses per account.

Benefits

1. Comprehensive Account Profiles: Create detailed reports capturing essential account information, including personnel associations, billing details, and contractual terms.
2. Operational Efficiency: Streamline data analysis with complete and well-organised account records to support efficient decision-making.
3. Enhanced CRM: Utilise detailed account insights to improve customer engagement, service quality, and account-specific reporting.

Key Features

1. Account Identity: Includes Account ID, account name, status, and type for every account in your FL3XX instance.
2. Billing & Financial Data: Captures payment conditions, invoices issued, total amount paid, and other financial details per account.
3. Sales Information: Tracks sales-related fields such as assigned sales contact and account-specific agreements.
4. Contact & Address Records: Supports multiple contacts and addresses per account for a complete and precise account profile.

 

 

Qualifications

The Qualifications dataset in BRIGHT, is designed to enhance your crew compliance and reporting capabilities. This dataset integrates qualification data directly from the FL3XX system, providing a consolidated view of crew members' qualifications, including key details such as Qualification Name, Issued Date, Expiry Date, and User Information. With this update, tracking and managing crew qualifications is more efficient, ensuring you stay ahead of compliance requirements.

The Qualifications dataset enables you to filter for the most recent records, generate insightful reports, and streamline crew management processes. Start leveraging this new feature to simplify compliance monitoring and gain clearer insights into your crew's qualifications.

Benefits:

1. Compliance Monitoring: Track which crew members have valid and up-to-date qualifications.
2. Crew Management: Identify crew members needing qualification renewals.
3. Regulatory Reporting: Generate reports for authorities showing compliance with qualification requirements.

 

Passengers

The Passengers dataset in BRIGHT provides a comprehensive overview of all passengers planned on a flight, including their check-in status, source, and key personal and flight details. This dataset simplifies reporting by consolidating relevant passenger information in one place. Flights without any assigned passengers are automatically excluded.

Benefits

1. Efficient Passenger Tracking: Quickly see who is on board for any flight, their check-in progress, and how they were checked in.
2. Regulatory & Operational Compliance: Create passenger manifests for authorities (e.g., SIFL-style reports) with accurate statuses and flight details.
3. Simplified Analysis: Build custom dashboards, pivot tables, or BI reports using passenger and flight data from a single dataset.

Key Features

1. Complete Passenger Manifest: Displays all passengers assigned to a flight with unique passenger and flight identifiers.
2. Check-In Details: Shows each passenger's check-in status (e.g., NOT_CHECKED_IN, CHECKED_IN) and check-in source (e.g., WEBAPP, CREW). An empty check-in status is treated as NOT_CHECKED_IN.
3. Flight Information: Includes flight numbers, airport details (ICAO/IATA), and operational timestamps (planned and actual on/off-block, takeoff, landing). Flight status is included, enabling tracking of cancelled flights when needed.
4. Passenger Profiles: Pulls personal details such as name, gender, nationality, and date of birth from the Persons dataset, along with associated account information.
5. Booking Linkage: Links to booking information (Booking ID, account details) for a complete reporting view across passengers, flights, and bookings.

 

 

Maintenance Events

The Maintenance Events dataset in BRIGHT is designed to streamline the tracking and analysis of maintenance-related activities for aircraft. This dataset integrates maintenance data directly from the FL3XX system, providing a centralized view of all maintenance events, including key details such as event descriptions, update types, due intervals, and aircraft-specific information.

With this dataset, managing and monitoring maintenance schedules becomes more efficient, ensuring compliance and operational readiness.The Maintenance Events dataset enables users to track recurring maintenance tasks, monitor due dates, and generate insightful reports for better maintenance planning and execution.

Benefits:

• Maintenance Tracking: Easily monitor upcoming and overdue maintenance tasks for each aircraft.
• Operational Efficiency: Plan maintenance schedules to minimize downtime and ensure aircraft availability.
• Regulatory Compliance: Maintain accurate records of maintenance events to meet aviation authority requirements.

Key Features:

• Event Details: Includes descriptions, task types, and update types for each maintenance event.
• Tracking Metrics: Provides intervals, next due dates, and maximum allowable due dates for maintenance tasks.
• Aircraft Information: Displays aircraft-specific details such as Aircraft ID, Tail Number, Type Rating, and Owner Information.
• User-Friendly Integration: Accessible in BRIGHT with clear data and filtering options for efficient reporting and analysis.

 

Aircraft Availability

The Aircraft Availability dataset in BRIGHT is designed to provide a comprehensive overview of aircraft operational readiness by tracking block time and availability status. This dataset integrates data directly from the FL3XX system, offering a centralized view of aircraft utilization and availability based on operational block time. By analyzing this dataset, users can optimize scheduling, ensure efficient resource allocation, and maintain operational readiness.

Principles:

Block Time [hours]: This field represents the total duration, in hours, during which an aircraft is unavailable for flight operations due to maintenance tasks. It specifically accounts for time blocked by two types of tasks: AOG and Scheduled Maintenance. The calculation ensures that overlapping maintenance periods are only counted once, providing an accurate reflection of the downtime.

Availability: This field indicates whether the aircraft is available for operations on a given day, based on the calculated block time. If the total block time within the operational window (06:00Z to 22:00Z) exceeds 8 hours, the aircraft is marked as unavailable for that day. Conversely, if the block time is 8 hours or less, the aircraft is considered available. This binary classification supports effective operational planning and resource management.

Benefits:

1. Operational Planning: Streamline scheduling by identifying aircraft availability based on block time thresholds.

2. Resource Optimization: Maximize aircraft utilization while minimizing downtime.

3. Decision Support: Enable data-driven decisions for fleet management and operational efficiency.

Key Features:

1. Block Time: represents the total duration, in hours, during which an aircraft is unavailable for flight operations due to maintenance tasks. This metric specifically accounts for downtime caused by two types of tasks: AOG and Scheduled Maintenance. The calculation of block time ensures that overlapping maintenance periods are only counted once, providing an accurate reflection of the aircraft's downtime. This precision is essential for effective operational planning and resource management, allowing airlines to optimize their schedules and maintain high levels of aircraft availability. 

2. Availability Status: Provides a binary classification of aircraft availability based on block time within the operational window (06:00Z to 22:00Z). Aircraft are marked as unavailable if the block time exceeds 8 hours and available if it is 8 hours or less.

3. Aircraft-Specific Details: Displays aircraft identifiers, such as Aircraft ID, Tail Number, and Type Rating, for precise tracking and reporting.

 

Fees

The Fees dataset in BRIGHT provides a detailed breakdown of pricing per booking, capturing both quoted and sold amounts across all fee types — including net and gross totals, taxes, surcharges, discounts, and custom fee categories defined by your operation. Each row represents a single fee line for a specific booking, giving you full visibility into how every booking is priced.

The dataset includes two complementary views: a line-level view (one row per fee type per booking) for granular analysis, and a pivoted view (one row per booking with fee totals as columns) for quick comparison of quoted vs. sold amounts side by side.

Benefits:

1. Revenue Analysis: Compare quoted vs. sold amounts across fee types to identify discounting patterns and protect margins.
2. Financial Reporting: Break down net, gross, tax, VAT, FET, surcharges, and discounts per booking for accurate financial reporting and audits.
3. Custom Fee Tracking: Monitor operator-defined fee categories alongside standard fee types for a complete picture of your pricing structure.

Key Features:

1. Quoted vs. Sold: Every fee line includes both the quoted amount and the sold amount (where a sold price exists), enabling direct comparison within the same dataset.
2. Fee Type Breakdown: Every booking includes three baseline fee types—Net, Gross, and Discount. Additional fee types (any custom categories configured in your FL3XX instance) are included only on quotes and bookings that use your Pricing Engine setup.
3. Regional Pricing Support: VAT is available for EU pricing operators; FET (Federal Excise Tax) is available for US pricing operators. The dataset automatically reflects your operator's pricing region.
4. Booking Context: The dataset links to booking details such as route, aircraft, account, status, and block times, enabling combined financial and operational analysis.

 

 

Duties

The Duties dataset in BRIGHT provides a detailed view of crew duty time data, covering every duty period logged for pilots, co-pilots, flight attendants, and freelance crew. Each row represents a single duty period for one crew member — from check-in to check-out — giving you a granular, time-accurate record of crew activity across your operation.

The dataset captures planned check-in and check-out times in both UTC and local time, departure and arrival airports, duty types, associated flights, and cumulative block and duty time totals. Cumulative time fields (such as block time over the last 14 or 28 days, and duty time over the last 7 or 28 days) are calculated per crew member and reflect rolling windows, supporting fatigue risk management and regulatory compliance reporting.

Benefits:

1. Fatigue & Compliance Monitoring: Track cumulative block and duty times per crew member across multiple rolling windows to stay ahead of regulatory limits.
2. Duty Period Analysis: Identify patterns in crew scheduling, duty lengths, and rest periods to optimize rostering and reduce operational risk.
3. Flight Assignment Visibility: Link duty periods directly to specific flights and aircraft, enabling a combined view of crew activity and flight operations.

Key Features:

1. One Row Per Duty Period: Each entry represents a unique duty period (check-in to check-out) for one crew member. The same crew member appears on multiple rows when they have multiple duties in the reporting window.
2. UTC and Local Times: Check-in and check-out times are provided in both UTC and local timezone, along with the timezone name, for accurate cross-region reporting.
3. Cumulative Time Windows: Block time and duty time totals are available across multiple rolling periods (e.g. last 14 days, last 28 days, year-to-date), expressed in minutes, and calculated per AOC configuration.
4. Flight and Aircraft Links: Each duty period includes the associated flight IDs, flight numbers, aircraft IDs, and aircraft registrations, allowing you to connect duty data with your flight and crew datasets.
   
   

 

 

Aircraft Activity (★ Coming Soon)

The Aircraft Activity dataset is a unified, timeline-style dataset that combines maintenance activities and completed flights into a single view. Instead of joining two separate sources in your BI tool, you can analyse aircraft usage and downtime on one grid.

Every row in the dataset is either a maintenance event or a completed flight leg, distinguished by the row type field ('maintenance' or 'flight'). Maintenance rows carry task details (type, status, dates, costs, provider, comments) with flight-specific columns set to null. Flight rows carry flight details (take-off/landing times, airports, booking reference, flight time) with maintenance-only fields (costs, work orders, release status) set to null.

Benefits

1. Unified Timeline View: Combine maintenance and flight activity in one analysis without manual dataset joins or data duplication.
2. Availability & Utilisation Reporting: Calculate block hours, utilisation rates, and downtime periods on a single, consistent aircraft timeline.
3. Flexible Filtering: Filter to maintenance-only or flight-only rows without switching datasets, using the row_type field.

Key Features

1. Row Type Field: Each row is labelled as 'maintenance' or 'flight', enabling clean separation and filtering within the same dataset.
2. Maintenance Row Detail: Carries task type, status, dates, costs, provider, and comments. Flight-specific columns are null on maintenance rows.
3. Flight Row Detail: Carries take-off/landing times (off and on block), departure/arrival airports (ICAO), booking reference, and flight time. Maintenance-only fields are null on flight rows.
4. Blueprint for Availability Reporting: Designed to support aircraft availability and downtime calculations, combining both maintenance and operational activity in the same continuous timeline.

When to Use This Report

 

 

 

Available Data points

• BRIGHT currently takes approximately 1200 data points across the EU and US instances. These data points cover booking, flight and crew-related data.
  Every field in FL3XX is available for BRIGHT users to combine in dashboards as you please.
• BRIGHT refreshes its data three times a day, ensuring users have access to up-to-date and accurate information every eight hours. The data refresh schedule is as follows: for the US Region (us-east-1.quicksight), data updates kickoff at 06:00, 14:00, and 22:00 UTC, while for the EU Region (eu-central-1.quicksight), updates kickoff at 03:00, 11:00, and 19:00 UTC. More information available here. 

• The airports dataset is refreshed weekly, with updates scheduled every Sunday.

• This regular refresh ensures that the insights, dashboards, and analyses you rely on remain current and relevant throughout the day.
• Operators with in-house data analysts who are interested in getting all raw data from their instance can have access to the data lake and data exchange systems from BRIGHT.
• For a comprehensive overview of available data fields, please refer to the full list provided in this Google Sheet.
• Data Inventory: For a comprehensive overview of all available data fields please consult the centralized reference in this Google Sheet. This resource is continually maintained to ensure you have up-to-date, detailed visibility into every field captured within the FL3XX BRIGHT and Data Lake platforms.