--- title: "Data Activity Guide" slug: "data-activity-guide" updated: 2026-07-23T16:43:36Z published: 2026-07-23T16:43:36Z canonical: "knowledge.curiositysoftware.ie/data-activity-guide" --- > ## Documentation Index > Fetch the complete documentation index at: https://knowledge.curiositysoftware.ie/llms.txt > Use this file to discover all available pages before exploring further. # Data Activity Guide This guide provides an overview of every activity available from the Activity Explorer, explaining what it does, key features, how it can help an organisation and where to learn more. Curiosity’s platform has several data activities to support your test data management. To navigate to the data activities, underneath Enterprise Test Data select Data Activities > Activity Explorer > Add Activity. The following data activities should be available to you: #### DATABASE - [Compare Database](/kb/docs/data-activity-guide#compare-database) - [Cross Definition FK Discovery](/kb/docs/data-activity-guide#cross-definition-fk-discovery) - [Data Generation](/kb/docs/data-activity-guide#data-generation) - [Find Data](/kb/docs/data-activity-guide#find-data) - [Machine Learning](/kb/docs/data-activity-guide#machine-learning) - [Mask Database](/kb/docs/data-activity-guide#mask-database) - [Scan Database](/kb/docs/data-activity-guide#scan-database) - [Subset Database](/kb/docs/data-activity-guide#subset-database) - [Transform Data](/kb/docs/data-activity-guide#transform-data) - [Validate Database Data](/kb/docs/data-activity-guide#validate-database-data) - [Windocks - Build Image](/kb/docs/data-activity-guide#windocks-–-build-image) - [Windocks - Create Container](/kb/docs/data-activity-guide#windocks-–-create-container) #### FILE - [Complex Data Sets](/kb/docs/data-activity-guide#complex-data-sets) - [Data Pattern Generation AI](/kb/docs/data-activity-guide#data-pattern-generation-ai) - [File Masking](/kb/docs/data-activity-guide#file-masking) - [Message Management](/kb/docs/data-activity-guide#message-management) - [Scan Files](/kb/docs/data-activity-guide#scan-files) #### GENERAL - [Data Probability Analysis](/kb/docs/data-activity-guide#data-probability-analysis) - [General All Purpose](/kb/docs/data-activity-guide#general-all-purpose) - [Pipeline](/kb/docs/data-activity-guide#pipeline) - [Pipeline (Data Gen)](/kb/docs/data-activity-guide#pipeline-data-gen) - [Data Monitoring](/kb/docs/data-activity-guide#data-monitoring) ### Organising Data Activities We highly recommend organising your Data Activities into a clear folder structure to make them easier to find, maintain, and revisit as your project grows. When you first log in to the platform, a baseline folder structure is provided within Activity Explorer. From here, you can create additional folders and subfolders to organise activities in a way that makes sense for your team. For example, you may choose to group activities by project, environment, release, application, or activity type. #### Creating Folders To create a new folder: 1. Navigate to Activity Explorer. 2. Select the green "+" button located beside the existing folder structure. 3. Enter a name for the folder and save it. 4. Repeat this process to create additional folders or nested subfolders as required. ![](https://cdn.document360.io/77f722a6-2d0a-49fa-8074-572515a6c4b8/Images/Documentation/base64-converted-image-1784822736799.png) #### Navigating Folder Structures Folders can be expanded and collapsed using the ">" icon beside the folder name. This allows you to navigate through your folder hierarchy and keep Activity Explorer organised and easy to read. #### Creating Activities Within Folders Once your folder structure has been created: 1. Navigate to the folder where you want the activity to be stored. 2. Expand any required parent folders using the ">" icon. 3. Create the new activity. The activity will automatically be saved within the folder you are currently working in. #### Moving Activities Between Folders If an activity needs to be relocated: 1. Locate the activity within Activity Explorer. 2. Select the multi-directional arrow icon beside the activity. 3. A window displaying the available folder structure will appear. 4. Navigate to the target folder. 5. Select OK to move the activity. ![](https://cdn.document360.io/77f722a6-2d0a-49fa-8074-572515a6c4b8/Images/Documentation/base64-converted-image-1784822747063.png) Using a logical folder structure from the outset will help keep your Data Activities organised, improve collaboration across teams, and make it much easier to locate activities as your repository grows. Data Activities #### Compare Database [Documentation](https://knowledge.curiositysoftware.ie/docs/database-compare) About: Helps organisations validate releases, migrations and testing outcomes by highlighting exactly what changed between two points in time. Key Features: Compare schemas, databases and snapshots Support high-watermark and snapshot comparisons Identify inserts, updates and changes Typical Use Cases: Release validation, migration testing, defect investigation #### Cross Definition FK Discovery About: Useful when database relationships are undocumented or incomplete. Key Features: Discover potential relationships Analyse legacy schemas Improve model understanding Typical Use Cases: Legacy modernisation, subsetting preparation #### Data Generation [Documentation](https://knowledge.curiositysoftware.ie/docs/synthetic-data) About: Provides safe, realistic data without relying on production records. Key Features: Generate synthetic data Configure generation rules Support referential integrity Typical Use Cases: Testing, development, performance testing #### Find Data [Documentation](https://knowledge.curiositysoftware.ie/docs/introduction-to-find-and-reserve) About: Reduces effort spent manually searching for suitable test data. Key Features: Locate existing test records Support self-service data access Typical Use Cases: Test execution support #### Machine Learning About: Helps identify trends and relationships that may improve test data quality. Key Features: Pattern analysis AI-assisted discovery Typical Use Cases: Data exploration #### Mask Database [Documentation](https://knowledge.curiositysoftware.ie/docs/mask-database) About: Protects sensitive information while keeping data usable in non-production environments. Key Features: Replace sensitive values Use reusable masking rules Support compliance initiatives Typical Use Cases: GDPR compliance, test environments #### Scan Database [Documentation](https://knowledge.curiositysoftware.ie/docs/scan-database) About: Provides visibility of the data landscape and builds the foundation for governance and test data projects. Key Features: Profile schemas and columns Identify sensitive data Calculate statistics and classifications Typical Use Cases: Data discovery, compliance reviews #### Subset Database [Documentation](https://knowledge.curiositysoftware.ie/docs/data-subset) About: Creates smaller, easier-to-manage environments while reducing costs and refresh times. Key Features: Extract targeted datasets Reduce environment size Retain relevant business context Typical Use Cases: ERP testing, environment optimisation #### Transform Data About: Improves compatibility between source and target systems. Key Features: Transform and reshape data Support migrations Typical Use Cases: Migration projects #### Validate Database Data [Documentation](https://knowledge.curiositysoftware.ie/docs/validate-and-explore-data-rules) About: Improves confidence in data quality. Key Features: Validate business rules Identify invalid records Discover hidden relationships Typical Use Cases: Data quality programmes #### Windocks – Build Image About: Enables repeatable environment provisioning. Key Features: Build container images Support automation Typical Use Cases: DevOps #### Windocks – Create Container About: Accelerates environment delivery. Key Features: Create containers on demand Provision environments quickly Typical Use Cases: Testing and development #### Complex Data Sets [Documentation](https://knowledge.curiositysoftware.ie/docs/complex-datasets) About: Improves test coverage while reducing the number of records required. Key Features: Pairwise generation Business-rule-driven datasets Coverage-focused combinations Typical Use Cases: Functional testing #### Data Pattern Generation AI [Documentation](https://knowledge.curiositysoftware.ie/docs/data-generation-ai) About: Creates realistic synthetic data while protecting privacy. Key Features: Analyse source datasets Generate statistically similar data Preserve data characteristics Typical Use Cases: Analytics and testing #### File Masking [Documentation](https://knowledge.curiositysoftware.ie/docs/data-masking-files-tutorial?highlight=file%20mask) About: Allows files to be shared and tested safely. Key Features: Mask sensitive file data Protect file-based datasets Typical Use Cases: File testing #### Message Management [Documentation](https://knowledge.curiositysoftware.ie/docs/manage-message-file-versions?highlight=message%20management) About: Improves repeatability of integration testing. Key Features: Manage messages and payloads Support integrations Typical Use Cases: API and messaging validation #### Scan Files [Documentation](https://knowledge.curiositysoftware.ie/docs/scan-files-function-new-feature?highlight=scan) About: Extends discovery capabilities beyond databases. Key Features: Analyse file contents Identify sensitive information Typical Use Cases: File governance #### Data Probability Analysis [Documentation](https://knowledge.curiositysoftware.ie/docs/data-probability-analysis) About: Uncovers patterns that can improve synthetic data and testing strategies. Key Features: Apriori analysis Discover relationships Identify potential business rules Typical Use Cases: Data analysis #### General All Purpose About: Supports bespoke business requirements. Key Features: Flexible workflow framework Typical Use Cases: Custom processes #### Pipeline [Documentation](https://knowledge.curiositysoftware.ie/docs/pipelines) About: Reduces manual effort by combining activities into repeatable processes. Key Features: Orchestrate activities Automate workflows Typical Use Cases: End-to-end automation #### Pipeline (Data Gen) About: Accelerates continuous test data delivery. Key Features: Automated data generation pipelines Typical Use Cases: CI/CD #### Data Monitoring [Documentation](https://knowledge.curiositysoftware.ie/docs/data-monitoring) About: Provides continuous visibility into the enterprise test data landscape. Key Features: Compliance monitoring Trend analysis Proactive alerts AI-driven insights Typical Use Cases: Governance and optimisation