Jira Business Data Inventory Template for Referrals
Yes, we provide a metadata-only Jira inventory template designed to facilitate company introductions without exposing sensitive data. This template focuses solely on record types and date ranges, ensuring partners never handle the company's actual data.
Engineering process consultants often seek efficient ways to catalog and understand a company's data landscape without delving into the actual data content. When referring US companies to SourceX, a metadata-only Jira inventory template can be a powerful tool to streamline the process, focusing on what matters for initial assessment: the types of records and their date ranges.
Why a Metadata-Only Approach?
SourceX facilitates data licensing for AI. Our focus is on connecting data holders with AI labs and data buyers. When you refer a company, the goal is to provide sufficient information for SourceX to understand the potential licensing opportunity, not to access the company's proprietary data itself.
A metadata-only approach ensures that:
- Privacy is paramount: No sensitive company data ever leaves the company's control. Your role as a referrer is purely introductory.
- Efficiency: You can quickly build a high-level inventory without complex data extraction or privacy compliance overhead.
- Clarity: The focus remains on the structure and scope of data, which is critical for SourceX to assess licensing potential.
Important: As a SourceX partner, you never handle or have access to the referred company's data. Your role is to introduce US companies that meet the baseline criteria (50+ full-time employees at peak, years of operating records, rights to license the data, and an authorized sponsor) to SourceX.
The Jira Business Data Inventory Template
This template is designed to be used within a Jira project. Each issue represents a distinct record type or dataset within the referred company. You can adapt the fields to your specific Jira instance, but the core idea is to capture metadata, not data content.
Here's a suggested structure for your Jira issues (e.g., as custom fields or issue description sections):
| Field Name | Field Type | Description |
|---|---|---|
| :------------------ | :---------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Summary | Short Text | Concise name of the record type (e.g., "Customer Order History", "Sensor Readings - IoT Devices", "Customer Support Tickets - Chat Logs") |
| Description | Long Text | A brief overview of what this record type represents, its primary purpose, and any key characteristics (e.g., "Records all sales transactions for B2B clients, including product, quantity, and price.") |
| Data Origin/System | Short Text | Where does this data primarily originate or reside? (e.g., "CRM System", "ERP Database", "Internal Analytics Platform", "IoT Sensor Network") |
| Record Type Examples | Long Text | Illustrative examples of individual records, without any actual data. Focus on structure. (e.g., "`{OrderID, CustomerID, ProductSKU, PurchaseDate, Amount}`", "`{DeviceID, Timestamp, TempC, PressurePSI}`") |
| Oldest Record Date | Date Picker | The earliest date for which this type of record is available (e.g., "2008-01-01") |
| Newest Record Date | Date Picker | The latest date for which this type of record is available (e.g., "2023-12-31") |
| Data Volume (Estimate) | Short Text | An estimated scale of this data type (e.g., "Billions of records", "Millions of unique entries per year", "Terabytes") |
| Update Frequency | Short Text | How often is this data updated or new records added? (e.g., "Real-time", "Daily batch", "Monthly snapshot", "Annually") |
| Potential Use Cases | Long Text | High-level ideas for how this data could be used by AI (e.g., "Customer behavior analysis", "Predictive maintenance", "Market trend forecasting", "Sentiment analysis") |
| Relevant Departments | Short Text | Which departments within the company are primary owners or users of this data? (e.g., "Sales, Marketing", "Engineering, Operations", "Customer Service") |
How to Use This Template
- Create a Project: In Jira, set up a dedicated project for your referral company assessments.
- Define Issue Types: Create an issue type, e.g., "Data Inventory Item", with the custom fields listed above.
- Populate Issues: For each distinct data record type the referred company possesses, create a new Jira issue and fill in the metadata fields. Emphasize that no actual data content should ever be entered into these fields.
- Share Metadata, Not Data: This inventory then serves as a structured way to discuss the company's data assets with SourceX, enabling us to understand their potential without ever exposing their proprietary information.
This approach aligns perfectly with the SourceX referral program, where your compensation is 25% of the eligible platform fees SourceX collects, up to $100,000 cumulative per referred company. The focus is on successful introductions that lead to licensing deals, not on data handling by partners.
- Step 1Share your linkSend your personal link to a company you know.
- Step 2Company appliesThe company applies itself at /apply.
- Step 3Buyer selects and paysThe buyer selects and pays for the data and SourceX receives its fee.
- Step 4You get your rewardYour share of SourceX fees becomes payable.
Free resources
- Cash flow calculator — A 12-month cash forecast with shortfalls highlighted.
- Referral earnings calculator — Hypothetical partner earnings with the per-company cap.
- Cash conversion cycle calculator — DIO, DSO, DPO and the cash conversion cycle.
- All free tools · MCP resource center
By SourceX Partnerships Team · Published 2026-10-09 · Updated 2026-10-09
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