Lesson 1: Analytics Architecture, Data Sources, Datasets, Models, and Security
Lesson Overview
This lesson develops practical skills in analytics architecture, data sources, datasets, models, and security for Salesforce CRM Analytics and Einstein Analytics Training.
Topics Covered
CRM Analytics architecture, apps, datasets, lenses, dashboards, recipes, and predictions
Salesforce and external data sources, connectors, sync, schedules, and permissions
Data modeling, grain, keys, relationships, measures, dimensions, dates, and hierarchies
Data security, sharing inheritance, predicates, row-level access, app permissions, and governance
Data quality, profiling, naming, documentation, lineage, and refresh strategy
Analytics solution planning and readiness
Practical Activity
Configure or analyze a scenario involving crm analytics architecture, apps, datasets, lenses, dashboards, recipes, and predictions.
Build and validate an exercise covering salesforce and external data sources, connectors, sync, schedules, and permissions and data modeling, grain, keys, relationships, measures, dimensions, dates, and hierarchies.
Use tests, logs, reports, or documentation to verify analytics solution planning and readiness.
Key Takeaways
Explain crm analytics architecture, apps, datasets, lenses, dashboards, recipes, and predictions in the context of Salesforce CRM Analytics and Einstein Analytics Training.
Apply practical methods for salesforce and external data sources, connectors, sync, schedules, and permissions and data modeling, grain, keys, relationships, measures, dimensions, dates, and hierarchies.
Test, document, and troubleshoot analytics solution planning and readiness.
