The flatten transformation allows us to flatten a hierarchical table. This is applied to the Salesforce role hierarchy table to flatten the data structure.
We will discuss this in the Row-level security for dataset section.
- Preface
- Introduction to AI
- Role of AI in CRM and Cloud Applications
- Building Smarter Apps Using PredictionIO and Heroku
- Product Recommendation Application using PredicitionIO and Salesforce App Cloud
- Introduction to Spark MLlib
- Setting up the Event Server app on Heroku
- Setting up the Recommendation engine application on Heroku
- Setting up IntelliJ IDEA IDE for customizing PredictionIO application
- Introduction to building Lightning Component for App Cloud and Community Cloud
- Building similar Recommendation Lightning Component for App Cloud
- PredictionIO commands cheat sheet
- Summary
- Salesforce Einstein Vision
- Building Applications Using Einstein Vision and Salesforce Force.com Platform
- Einstein for Analytics Cloud
- Setting up Wave Analytics Cloud
- Creating datasets, lenses, and dashboards
- Using transformations to create dataset
- The sfdcDigest transformation
- The sfdcRegister transformation
- The append transformation
- The augment transformation
- The computeExpression transformation
- The computeRelative transformation
- The delta transformation
- The dim2mea transformation
- The edgemart transformation
- The filter transformation
- The flatten transformation
- The sliceDataset transformation
- An update transformation
- Wave Analytics SAQL, XMD 2.0, and dataset Row-Level Security
- Introduction to Einstein Data Discovery
- Importing Salesforce data into Einstein Data Discovery and creating stories
- Summary
- Einstein and Salesforce IoT Cloud Platform
- IoT Cloud key terms
- IoT Cloud components
- Apache Kafka on Heroku
- IoT integration on the Salesforce Force.com platform
- Using PredictionIO on IoT events
- Summary
- Measuring and Testing the Accuracy of Einstein
The flatten transformation
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