Monday, 17 June 2019

Brief introduction to Nodes used in Salesforce Analytics Data flow

Any manipulation done to the data can be referred as a transformation process. In order to manipulate the data, we can add transformations to a dataflow to extract data from Salesforce objects or datasets, transform them (Salesforce data or external data), and register those datasets.

Below is the glossary used in Dataflow Analytics describing the role/term in the process.
  • sfdcDigest node - Extracts data or generates a dataset from a Salesforce object to be used for queries and further transformation.
  • sfdcRegister node - is responsible for registering dataset to make them available to use them in queries.
  • augment - As the name suggests, it augments the related datasets. The left and right keys are the fields from each node that are used to match records (similar to JOIN operations from SQL).
  • digest - is used to extract data synced from the local Salesforce org, or data synced through an external connection.
  • computeExpression  - is useful to create calculated fields or derived fields and add those to the dataset.
  • update - As the name suggests, this transformation updates the specified field values in an existing dataset based on data from another dataset.
  • filter  - The filter transformation is used to filter the records from an existing data-set based on the condition.
  • edgemart  - The edgemart transformation is actually the collection of the datasets which include an existing, registered data-set, or which can contain Salesforce data, external data, or both.
  • sliceDataset - The sliceDataset transformation performs the slicing and dicing of fields from a dataset in your dataflow.
We can find on each node of Salesforce Analytics Dataflow here.

If you have any questions you can reach out our Salesforce Consulting team here.

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