Metadata Type: WaveLens
Introduction
WaveLens is a metadata type in Salesforce that represents a lens object in the Analytics application (formerly known as Wave Analytics). A lens in Analytics is a particular view into a dataset's data. It specifies how the dataset is queried and displayed, allowing users to explore and visualize their data in different ways. The WaveLens metadata type allows developers and administrators to work with these lens objects programmatically through the Metadata API.
Key Characteristics
Some important characteristics of the WaveLens metadata type include:
- It extends the MetadataWithContent metadata type, inheriting the content and fullName fields
- The content field contains the actual JSON definition of the lens
- The fullName field uniquely identifies the lens
- WaveLens components have the file suffix .wlens
- They are stored in the waveComponents folder in a metadata deployment package
Working with WaveLens Metadata
Developers and administrators can interact with WaveLens metadata in several ways:
Retrieval
WaveLens metadata can be retrieved from an org using tools like the Salesforce CLI or Workbench. This allows you to extract the definitions of existing lenses for backup, analysis, or deployment to another org.
Deployment
New or modified WaveLens definitions can be deployed to an org as part of a metadata deployment package. This enables version control and automated deployment of Analytics assets.
Programmatic Manipulation
The Metadata API allows for programmatic creation, reading, updating, and deletion of WaveLens metadata. This can be useful for automating lens management tasks or integrating with external systems.
Deployment Challenges
While working with WaveLens metadata can be powerful, there are some common challenges and issues that administrators may encounter during deployment:
Dataset Dependencies
Lenses are tightly coupled to their underlying datasets. If a lens is deployed without its corresponding dataset, or if the dataset structure has changed, the deployment may fail or the lens may not function as expected. It's crucial to ensure that all required datasets are deployed and up-to-date before deploying lenses.
Security and Sharing Settings
Lenses inherit security settings from their parent app and dataset. When deploying a lens to a new environment, ensure that the appropriate security and sharing settings are in place. Otherwise, users may not be able to access or view the lens as intended.
API Version Compatibility
The structure and capabilities of WaveLens metadata can change between API versions. When deploying lenses between orgs, make sure both environments are on compatible API versions to avoid unexpected behavior or deployment failures.
Complex JSON Structure
The lens definition in the content field is a complex JSON structure. Manual editing of this JSON can be error-prone and may lead to invalid lens definitions. It's generally better to make changes through the Analytics UI and then retrieve the updated metadata.
Partial Deployments
If a deployment package contains multiple interdependent Analytics components (datasets, lenses, dashboards), a partial deployment failure can leave the Analytics environment in an inconsistent state. It's important to plan deployments carefully and consider deploying related components together.
Best Practices for Administrators
To effectively work with WaveLens metadata and avoid common pitfalls, Salesforce administrators should follow these best practices:
1. Use Version Control
Store WaveLens metadata in a version control system along with other metadata types. This provides a history of changes, facilitates collaboration, and allows for easy rollback if issues occur during deployment.
2. Maintain Consistent Naming Conventions
Adopt and enforce consistent naming conventions for lenses across all environments. This makes it easier to manage and identify lenses, especially when dealing with large numbers of Analytics assets.
3. Document Dependencies
Maintain documentation of the relationships between lenses, datasets, and other Analytics components. This helps in planning deployments and troubleshooting issues.
4. Use Sandbox Testing
Always test WaveLens deployments in a sandbox environment before deploying to production. This allows you to catch and resolve issues without impacting end users.
5. Deploy Related Components Together
When possible, deploy lenses along with their related datasets and dashboards in the same package. This ensures that all interdependent components are updated together, maintaining consistency.
6. Leverage Change Sets
For simpler deployments, use change sets to move WaveLens metadata between environments. Change sets can help manage dependencies and provide a user-friendly interface for deployment.
7. Monitor API Version Changes
Stay informed about changes to the WaveLens metadata structure in new API versions. Update your deployment processes and scripts as necessary when upgrading to a new version.
8. Implement Governance Processes
Establish clear processes for the creation, modification, and deployment of lenses. This should include approval workflows, testing requirements, and documentation standards.
9. Regular Metadata Backups
Periodically retrieve and backup WaveLens metadata from your production org. This provides a safety net in case of accidental deletions or corruptions.
10. Use Descriptive Labels
Encourage users to provide clear, descriptive labels for lenses. This metadata is included in the WaveLens definition and can be crucial for understanding the purpose and content of a lens during deployment or maintenance.
Conclusion
The WaveLens metadata type is a powerful tool for managing Analytics lenses in Salesforce. By understanding its characteristics, being aware of potential deployment challenges, and following best practices, administrators can effectively leverage this metadata type to manage and deploy Analytics assets across their Salesforce environments. As with any complex system, success with WaveLens metadata comes from a combination of technical knowledge, careful planning, and rigorous testing processes.