---
title: "More about what we store in AWS"
canonical: "https://support.55degrees.se/space/SP/3964993574/More%20about%20what%20we%20store%20in%20AWS"
format: markdown
---
> ✅ **Don’t Fret**  
> ✅ All data is encrypted at rest and in transit. Most data is pseudonymized for further protection. See below for actual examples of what is stored. If you have any further questions, reach out via our [support portal](https://support.55degrees.se).

> 📝 **Data Retention**  
> 📝 We retain the data associated with your Jira instance until you’ve no longer had a supported subscription with us for 60 days. This way if you uninstall and reinstall, or there’s a short gap before renewal, you won’t lose your data. If you want your instance’s data removed earlier, you can reach out in writing to us via our [support portal](https://support.55degrees.se).

### Forecast Configuration Data

Used to define *how* forecasts are calculated.

Includes:

- Forecast names and identifiers
- Jira data sources (board, project, JQL)
- Throughput and simulation settings
- Hierarchical relationships between forecasts
- Viewer/admin permission sets
- Audit metadata (creator, timestamps, app version)

**Purpose:** Required to reproduce forecasts consistently and manage access control.

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### Forecast Results

Stores the output of Monte Carlo simulations.

Includes:

- Probability distributions
- Completion date ranges
- Historical forecast snapshots
- Processing status metadata

**Purpose:** Allows users to review historical forecasts, compare changes over time, and share results.

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### Portfolio Data

Used to group multiple forecasts for program- or portfolio-level analysis.

Includes:

- Portfolio definitions
- Associated forecast identifiers
- Display configuration (selected Jira fields)
- Permissions and audit metadata

**Purpose:** Enables consolidated reporting across multiple teams or initiatives.

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### Scenario Data

Optional "what-if" configurations that modify forecast assumptions.

Includes:

- Alternative parameters (e.g., scope or capacity changes)
- Scenario-specific overrides

**Purpose:** Allows experimentation without altering the primary forecast configuration.

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### User Preference Data

Includes:

- Favorite forecasts
- Favorite portfolios

Identified by Atlassian account ID and Jira Cloud ID.

**Purpose:** Improves usability and personalization.

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### Scheduling Metadata

Used for automated forecast generation.

Includes:

- Scheduling frequency and rules
- Next execution timestamps

**Purpose:** Keeps forecasts up to date without manual interaction.

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### Dependency Configuration

Defines how Jira issue link types represent dependencies.

Includes:

- Jira link type identifiers
- Directionality and settings
- Audit metadata

**Purpose:** Ensures dependency-aware forecasting when issue relationships are used.

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### Legacy Connect lookup 

Required for handling pre-Forge data retreival

Includes:

- Client identifiers
- Cloud Id