What can you use the Datamart for?
The Datamart provides structured, analytics-ready Geniebelt data designed for reporting and analysis.
You can use it to:
Create reports and dashboards – Use Geniebelt data to build reports, dashboards, and visualisations.
Analyse historical data – Track trends, KPIs, and project performance over time.
Analyse data across projects – Combine data from multiple projects to get an overview of performance and identify trends.
Connect to Business Intelligence (BI) tools – Use the Datamart with tools such as Power BI, Tableau, Looker, or your own internal data platforms.
Combine data from different systems – Connect Geniebelt data with information from other systems, such as ERP or financial systems.
Examples of how to use the Datamart
The Datamart can be used to create reports and dashboards tailored to your organisation's needs.
Some examples include:
Business unit adoption and performance – Compare activity across business units, including the number of projects, comments, photos, and reported issues over time.
Financial planning and forecasting – Combine Geniebelt schedules and progress data with financial data from ERP systems to forecast revenue and track actual performance. Changes to task schedules can be reflected in updated forecasts after the next data refresh.
Portfolio performance overview – Get an overview of projects across your portfolio, including project status, participants, tasks, attachments, and archived projects.
Partner adoption and performance – Monitor how actively partners and subcontractors use Geniebelt by tracking contributions such as task updates, progress reports, comments, and other activities over time.
These are just examples. You can combine Geniebelt data with information from other systems to create reports and dashboards tailored to your needs.
How does the Datamart work?
The Datamart provides a structured snapshot of your Geniebelt data, optimised for reporting and analysis.
Data is refreshed every 24 hours, allowing you to analyse project information without affecting the performance of your daily operations in Geniebelt.
Unlike the API, which provides real-time access to data, the Datamart is designed to handle larger amounts of data efficiently.
Available data
The Datamart contains data from different areas of Geniebelt, including companies, projects, tasks, users, progress reports, comments, and attachments.
The following tables are available:
Table name | What data it contains |
gb_companies | Company master data (id, name, created/updated timestamps). |
gb_company_members | Link between users and companies incl. role (owner, manager, member), invitation and membership timestamps. |
gb_projects | Project master data incl. name, description, start/end dates, owner, progress %, estimated progress %, subscription, archive status, location (address, lat/long), work duration, and company link. |
gb_project_members | Link between users and projects incl. role (owner, manager, subcontractor, observer), team_id and membership timestamps. |
gb_groups | Task group definitions (project_id, name, created/updated timestamps). |
gb_project_items | Hierarchy structure connecting projects to tasks (package_id) and groups (group_id), including parent_group_id for nested structures. |
gb_packages (Tasks) | Task-level data incl. schedule (start/end), actual dates, progress %, estimated progress %, state (in_progress, delayed, signed_off, etc.), milestone flag, delay calculation, work duration, reporting mode, validation status, tags, and custom metadata. |
gb_packages_assignees | Link between tasks and assigned project members (task_id ↔ project_member_id). |
gb_package_progress_reports | Historical task progress entries incl. work_state, progress_state (ahead/on_time/delayed), actual progress, estimated progress at reporting time, issues flag, rejection flag, reporting user (project_member_id), attachments count, and timestamps. |
gb_baseline_packages | Baseline schedule data for tasks incl. baseline start_date and end_date, baseline_id, and timestamps. |
gb_beats | User activity log capturing actions (new, update, progress, etc.), user_id, project_member_id, item_type, item_id, archived flag, timestamps, and action content. |
gb_comments | Comment text created by users incl. user_id, content, and timestamps. |
gb_comments_packages | Link table connecting comments to tasks (package_id ↔ comment_id). |
gb_attachments | File metadata incl. file name, type, size, display name, and timestamps. |
gb_attachments_comments | Link between attachments and comments (attachment_id ↔ comment_id). |
gb_attachments_package_progress_reports | Link between attachments and progress reports (attachment_id ↔ package_progress_report_id). |
gb_users | User master data incl. email, phone, first/last name, invitation lifecycle dates, profile picture reference, and settings. |
gb_baseline_packages | Baseline schedule data for tasks incl. baseline start_date and end_date, baseline_id, and timestamps. |
These tables can be combined to create reports and dashboards based on the information you need.
Connecting to the Datamart
The Datamart supports Delta Sharing, allowing you to connect your Geniebelt data directly to compatible BI tools and data platforms.
You can use it with tools such as:
Microsoft Power BI
Tableau
Looker
Internal data platforms supporting Delta Sharing
Once connected, you can use the available data to create your own reports, dashboards, and analyses.
How to get access to the Datamart
To get access, please contact Geniebelt Support. We will help you get the feature enabled and provide the information you need to connect to the Datamart.
API or Datamart?
The API and Datamart are designed for different purposes.
Geniebelt API | Geniebelt Datamart |
Real-time data | Historical and analytical data |
System integrations | Reporting and analytics |
Automated actions and workflows | Analysis across larger datasets |
Operational use | Decision-making over time |
The Datamart is generally the right choice when your main purpose is analytics, historical analysis, or working with large amounts of data for reporting and decision-making.
If you need real-time actions or system integrations, the Geniebelt API may be more suitable.
Need help? Chat in the app or contact our support here.