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Intro to einstein analytics Feb 2020
- 2. 2.2 PRESENTED BY CloudKettle Intro to Einstein Analytics
- 3. • Manager, Business Intelligence • Bcomm. Major in CISY from SMU • Interests in Data Engineering & Analytics
- 4. Einstein Analytics Agenda 1. What is Einstein Analytics? 2. Data Sources 3. Dataflow and Recipes 4. Datasets 5. Lenses/Dashboards 6. Security 7. Creating an Einstein Analytics Playground 8. Resources 9. Special Guest
- 5. Einstein Analytics What is Einstein Analytics? • Cloud based Business Intelligence platform. • Ability to create Applications that provide an interactive experience for users as they explore their data. • Provides self service AI capabilities (Einstein Discovery). • Data Visualizations optimized for Web Browser and Mobile use. • Ability to embed visuals into Salesforce
- 7. Einstein Analytics What about Salesforce Reports & Dashboards? • “Salesforce Reports/Dashboards are a tool. Einstein Analytics is a brand new Platform.” • Einstein: Interact, drill down and have an experience with your data while deriving insights. • Ability to analyse and store, not just Salesforce data, but external data as well. ▪ Creates a more meaningful analysis through fully interactive dashboards.
- 8. Einstein Analytics Reports vs Analytics Salesforce Reports/Dashboards Einstein Analytics Shows what’s going on Explains why things happens Organizing/summarizing data Questioning, Interpreting and Exploring data Results provided for users to view Users interact with data to answer questions Turns data into Information Provides knowledge to drive action
- 9. Einstein Analytics Data Sources • File Uploads • Salesforce Objects • External Sources ▪ Data Connectors ▪ Mulesoft API connection
- 10. Einstein Analytics Dataflow & Recipes
- 11. Einstein Analytics Dataflow • Combine and transform data from multiple sources. • Saves output as a new Dataset. • Schedule to run whenever data needs to be refreshed. • Best used when data is predictable (No UI to preview data… yet..)
- 12. Einstein Analytics Recipes • Use to clean and prepare data for analysis. • Best used when you have a single data source and require a single dataset output. • Provides a data preview and ability to easily revert changes. • Suggests transformations based on source data.
- 13. Einstein Analytics Should we use a Dataflow or Recipe? Dataflow Recipe Multiple Data Sources Single Sources Multiple Target Datasets Single Dataset Output Predictable Source Data Visual Preview Available Data Transformation Knowledge Intuitive Data Cleaning
- 14. Einstein Analytics Datasets • A collection (Table) of data that is stored in a highly compressed format. • 3 field types ▪ Date ▪ Dimension ▪ Measure
- 15. Einstein Analytics Lenses & Dashboards
- 16. Einstein Analytics Lenses • Tool used to explore datasets. ▪ How you view data in a dataset ▪ Explore data graphically, in a table, or via SAQL ▪ Basis for building any dashboard
- 17. Einstein Analytics Dashboards • Used to analyze key results on an ongoing basis. • Ability to leverage interactive charts to organically summarize information. • Filters allow dashboard views to tailor results to their needs. • Advanced features like faceting and interactions provide even more customization abilities for the end user.
- 18. Einstein Analytics Security • Two ways to limit what users can see in a Dataset. • Regardless of method(s) used, it’s important to discuss business requirements with key stakeholders before implementing security. Sharing Inheritance Security Predicates Same data sharing setup as Salesforce uses for your Objects. Filter condition that defines row level access to records in a dataset
- 19. Einstein Analytics Creating an Analytics Playground Org Similar to a Trailhead org, except this has Einstein Analytics & Discovery License. Click below for a Trailhead that walks you through Org Creation
- 20. Einstein Analytics Further Learning • Einstein Analytics Plus Trail Mix • Einstein Analytics Plus Training Videos