Learn Project Best Practices
Below is a collection of key best practices for any data and analytics developer working on a CRM Analytics or Einstein Discovery project. All the insight is based on years of experience and many projects of high complexity.
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- Planning for a successful project
- Managing Salesforce environments
- Designing beautiful analytics apps
- Building for enterprise environments
- Managing & optimizing assets
Planning for a successful project
Any data project should be carefully planned and considerations made before getting started with any build.
Staying focused – Using a methodology to organize your thoughts and project activities
Data Orchestration in Tableau CRM
Data Sources and Landscape – Data Orchestration Part 1
The Concepts of Data Sync – Data Orchestration Part 2
Considering Governance Limits – Data Orchestration Part 3
External Data and Data Volume – Data Orchestration Part 4
Managing Salesforce environments
How should you manage production and sandbox environments and how do you best deploy from one environment to another.
Uncovering Deployment Techniques for Tableau CRM
Developing and Managing Tableau CRM Assets in Production
Developing and Managing Tableau CRM Assets in Sandbox
Designing beautiful analytics apps
How do you design dashboards with an intended purpose that are beautiful and a pleasure to use.
Building for enterprise environments
If you use Salesforce enterprise features that you want to include in your data and analytics use cases.
Managing & optimizing assets
Keep your environment tidy and performance-optimized. Use tools to get the job done quickly.
Optimizing long-running dataflows
Clean up Data Manager Assets
Tableau CRM – Best Practices for a faster dashboard
Tableau CRM faster Dashboard – Efficient Queries
Tableau CRM faster Dashboard – Network to the rescue
Introducing the dataflow visualizer
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