Connecting Sumo with Einstein Analytics
Updated over a week ago

Goal

The goal is to drive an increase in revenue around understanding the behaviours of your sales team and identifying areas for improvement.

The behaviours are captured by the Cloudapps Sumo solution and can be analysed using Einstein Analytics.

This document is split into 2 main sections:

  1. Extracting the data into Einstein Analytics

  2. Building Einstein Dashboards on the Sumo Data

Extracting the Data into Einstein Analytics

Assign Permissions to Analytics Cloud Integration User

  • Assign a Sumo License to your Analytics Cloud Integration User

  • Setup a new Permission Set - Sumo Analytics

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  • Add read permission on all the fields (except for DEPRECATED fields) of the following objects:

    • Insights

    • Base Behaviours

    • Graphics

    • Rewards (make sure this is the Reward object that is part of the Sumo package)

    • Behaviours

    • Members

    • Collectives

    • Observations

  • Assign this Permission Set to your Analytics Cloud Integration User

Create the Sumo Analytics App

  • Select the Analytics Studio App from your salesforce app icon

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First, we are going to create a new App as a container for our datasets and dashboards.

  • Press the Create button in the top right-hand side of the page and select App

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  • Press the Create a Blank App button

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  • Press the Continue button

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  • Give the App a Name e.g. Sumo Analytics and press the Create button

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Create Sumo Analytics Dataflow

  • Select Data Manager from the Setup button on the top right of your navigation bar

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  • Select Dataflows & Recipes from the left-hand menu

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  • Press the Create Dataflow button in the top right-hand part of the page

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  • Give the Dataflow a Name e.g. Sumo Dataflow and press the Create button

We recommend building 3 Dataset for your analysis:

  1. Sumo Insights

  2. Sumo Rewards

  3. Sumo Observations

  4. Sumo Opportunities

Create Sumo Insights Dataset

  • Select the datasetBuilder button. This provides a wizard to select the objects and fields we need from salesforce in our dataset

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  • Give the Dataset a Name - e.g. Sumo Insights and press the Continue button

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You will be presented with a list of all the objects the Analytics Cloud Integration User can see.

  • Select Insight from this list

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  • Hover over the Insights blue bar and a + button will appear to the right of the bar. Press this + button

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  • Select the following fields:
    • Category
    • Occurrence Date
    • Related Record ID
    • Test Record
    • Type

  • Choose the Relationships tab

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  • Click on JOIN next to the Base Behaviour

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  • Click on Join on User

  • Hover over the Base Behaviour blue bar and a + button will appear to the right of the bar. Press this + button

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  • Then choose the following fields:

    • Behaviour Name

    • Business Area

    • Object

    • Undesirable

    • Value

  • Hover over the User blue bar and a + button will appear to the right of the bar. Press this + button

  • Then choose the following fields:

    • Full Name

    • Recommended:

      • Country

      • Department

      • Division

  • Then add any useful custom user fields

  • Choose the Relationships tab

  • Click on JOIN next to the Manager

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  • Hover over the second User blue bar and a + button will appear to the right of the bar. Press this + button

  • Then choose the following fields:
    • Full Name

  • Then press the Next button at the bottom of the page


Einstein Analytics will then build the process to extract the fields from the objects you have identified and then join the data into a single dataset.
It should look like this:

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  • Press the Update Dataflow and give the version a name and then press the Update Dataflow button

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  • Press the Run Dataflow button

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  • Press the Go to Data Monitor

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  • Refresh the page and monitor to make sure it completes successfully

Create the Sumo Insight Recipe

Now we are going to build a Recipe to hide certain fields and also rename certain fields.

  • Select Data from the left-hand menu

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  • Click on the Sumo Insights record and give the Recipe a Name - e.g. Sumo Insights

You will be presented with a spreadsheet view of your dataset.

  • Hide the following column:

    • User

    • Base Behaviour

    • success__User__c.ManagerId

    • RecordId

  • Rename the following fields (select the Attributes tab on the right-hand pain and change the Field Label field:

Current Label

New Label

success__Base_Behaviour__c.success__Functional_Area__c

Business Area

success__Base_Behaviour__c.success__IsNegative__c

Undesirable

success__Base_Behaviour__c.Name

Base Behaviour

success__User__c.Country

Country

success__User__c.Name

User

success__User__c.Department

Department

success__Base_Behaviour__c.success__Object__c

Object

success__Base_Behaviour__c.success__Priority__c

Value

success__User__c.ManagerId.Name

Manager

success__User__c.Division

Division

  • Press the Save button

  • Then press the Create Dataset button

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  • Select the Sumo Analytics App and then press the Continue button

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  • Select Yes when prompted if you wish to run the recipe periodically, and then press the Schedule Recipe button

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  • Suggest the follow scheduling parameters

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The Sumo Insights dataset is now ready to be used to create your dashboards.

Create Sumo Rewards Dataset

We now need to repeat thisprocess to create the Sumo Rewards dataset

  • Edit the Sumo Analytics Dataflow

  • Select the datasetBuilder button

  • Give the Dataset a Name - e.g. Sumo Rewards and press the Continue button

  • Choose the Reward Object and pick the following fields:

    • Badge

    • Hidden

    • Last Modified Date

    • Points

    • Related Record Id

    • Reward Type

    • Status

    • Test Record

    • Relationships -> Badge Type

      • Graphic Name

    • Relationships -> Base Behaviour

      • Behaviour Name

      • Business Area

      • Object

      • Undesirable

      • Value

    • Relationships -> Behaviour

      • Relationships - Collective

        • Name

    • Relationships -> Member

      • Grouping

      • Member Role

    • Relationships -> User

      • Full Name

      • Country

      • Department

      • Division

      • Relationships - Manager ID

        • FullName

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  • Press the Update Dataflow and give the version a name e.g. Added Sumo Rewards, and then press the Update Dataflow button

  • Press the Run Dataflow button

  • Press the Go to Data Monitor button

  • Refresh the page and monitor to make sure it completes successfully

Create the Sumo Rewards Recipe

Now we are going to build a Recipe to hide certain fields and also rename certain fields.

  • Select Data from the left-hand menu

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Click on the Sumo Rewards record and give the Recipe a Name - e.g. Sumo Rewards

You will be presented with a spreadsheet view of your dataset.

  • Hide the following column:
    • User
    • Base Behaviour
    • success__User__c.ManagerId
    • RecordId
    • Badge Type
    • Behaviour
    • success__Team_Achievement__c.success__Team__c
    • Member

  • Rename the following fields (select the Attributes tab on the right hand pain and change the Field Label field:

Current Label

New Label

success__Achievement__c.success__Functional_Area__c

Business Area

success__Achievement__c.success__IsNegative__c

Undesirable

success__Achievement__c.Name

Base Behaviour

success__User__c.Country

Country

success__User__c.Name

User

success__User__c.Department

Department

success__Achievement__c.success__Object__c

Object

success__Achievement__c.success__Priority__c

Value

success__User__c.ManagerId.Name

Manager

success__User__c.Division

Division

Last Modified Date

Occurrence Date

success__Team_Member__c.success__Role_Name__c

Member Role

success__Badge_Type__c.Name

Type

success__Team_Member__c.success__Grouping__c

Group

success__Team_Achievement__c.success__Team__c.Name

Collective

  • Press the Save button

  • Then press the Create Dataset button, select the Sumo Analytics App and then press the Continue button

  • Select Yes when prompted if you wish to run the recipe periodically, and then press the Schedule Recipe button

  • Suggest running every day at 04:00

The Sumo Rewards dataset is now ready to be used to create your dashboards

Create Sumo Observation Dataset

We now need to repeat this process to create the Sumo Observation dataset

  • Edit the Sumo Analytics Dataflow

  • Select the datasetBuilder button

  • Give the Dataset a Name - e.g. Sumo Observations and press the Continue button

  • Choose the Observation Object and pick the following fields:

    • Last Modified Date

    • Related Record Id

    • Test Record

    • Tracked Field Value

    • Relationships -> Base Behaviour

      • Behaviour Name

      • Business Area

      • Category

      • Object

      • Undesirable

      • Value

      • Relationships -> Type

        • Graphic Name

    • Relationships -> User

        • Full Name

        • Country

        • Department

        • Division

        • Relationships - Manager ID

          • FullName

  • Press the Update Dataflow and give the version a name e.g. Added Sumo Observations, and then press the Update Dataflow button

  • Press the Run Dataflow button

  • Press the Go to Data Monitor button

  • Refresh the page and monitor to make sure it completes successfully

Create the Sumo Observations Recipe

Now we are going to build a Recipe to hide certain fields and also rename certain fields.

  • Select Data from the left-hand menu

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Click on the Sumo Observations record and give the Recipe a Name - e.g. Sumo Observations

You will be presented with a spreadsheet view of your dataset.

  • Hide the following column:
    • User
    • Base Behaviour
    • success__User__c.ManagerId
    • RecordId
    • success__Base_Behaviour__c.success__Badge_Type__c

  • Rename the following fields (select the Attributes tab on the right hand pain and change the Field Label field:

Current Label

New Label

Last Modified Date

Occurrence Date

success__Base_Behaviour__c.success__Badge_Type__c.Name

Type

success__User__c.Country

Country

success__User__c.Name

User

success__User__c.Department

Department

success__Base_Behaviour__c.success__Functional_Area__c

Business Area

success__Base_Behaviour__c.success__Object__c

Object

success__Base_Behaviour__c.success__Category__c

Category

success__Base_Behaviour__c.success__Priority__c

Value

success__User__c.ManagerId.Name

Manager

success__User__c.Division

Division

success__Base_Behaviour__c.success__IsNegative__c

Undesirable

success__Base_Behaviour__c.Name

Base Behaviour

  • Press the Save button

  • Then press the Create Dataset button, select the Sumo Analytics App and then press the Continue button

  • Select Yes when prompted if you wish to run the recipe periodically, and then press the Schedule Recipe button

  • Run every day at 04:30

The Sumo Observations dataset is now ready to be used to create your dashboards

Create Sumo Opportunities Dataset

We now need to repeat this process to create the Sumo Opportunities dataset

  • Edit the Sumo Analytics Dataflow

  • Select the datasetBuilder button

  • Give the Dataset a Name - e.g. Sumo Opportunities and press the Continue button

  • Choose the Opportunity Object and pick the following fields:

    • Amount

    • CloseDate

    • Name

    • Won

    • Relationships -> Owner ID

      • FullName

    • Relationships -> Account ID

      • Account Name

  • Press the Update Dataflow and give the version a name e.g. Added Sumo Opportunities, and then press the Update Dataflow button

  • Press the Run Dataflow button

  • Press the Go to Data Monitor

  • Refresh the page and monitor to make sure it completes successfully

Create the Sumo Opportunities Recipe

Now we are going to build a Recipe to hide certain fields and also rename certain fields.

  • Select Data from the left-hand menu

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  • Click on the Sumo Opportunities record and give the Recipe a Name - e.g. Sumo Opportunities

You will be presented with a spreadsheet view of your dataset.

  • Hide the following column:

    • Account ID

    • Owner ID

  • Rename the following fields (select the Attributes tab on the right-hand pain and change the Field Label field:

Current Label

New Label

AccountId.Name

Account Name

OwnerId.Name

Owner

Name

Opportunity Name

  • Press the Save button

  • Then press the Create Dataset button, select the Sumo Analytics App and then press the Continue button

  • Select Yes when prompted if you wish to run the recipe periodically, and then press the Schedule Recipe button

  • Suggest the follow scheduling parameters

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The Sumo Rewards dataset is now ready to be used to create your dashboards.

Building Einstein Dashboards on the Sumo Data

  • Select the Analytics Studio App from your salesforce app icon

  • Press the Create button and select Dashboard from the drop down menu

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  • Press Create Blank Dashboard button

  • Drag and drop the Chart icon onto the canvas, place and then resize

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  • Press the Chart button in the center of the panel and choose the Sumo Insights dataset

  • Press the + button under the Bars section and select Occurrence Date -> Year-Month-Day

  • Press the + button under the Bars section and select Type, then press the Done button

  • Change the Chart Type to Stacked Column

  • Drag and drop the Filter icon onto the canvas

  • Press the Filter button in the center of the panel and choose the Sumo Insights dataset -> Manager

  • Press the Eye icon on the top right-hand side to put your dashboard in a viewing mode.

  • Choose different Managers and see the effect on the chart

  • Press the Pencil icon on the top right-hand side to put your dashboard back into edit mode.

  • Press the Save icon on the top right-hand side to save your work.

  • Give your dashboard a name - e.g. Sumo Insights and place in the Sumo Analytics App, then press the Save button

  • Continue adding charts and filters to build the dashboard of your dreams!

Salesforce has a number of courses on Trailhead on building Einstein dashboards - this is a good starting one - https://trailhead.salesforce.com/content/learn/modules/wave_dashboard_designer_basics?trail_id=wave_analytics_enable_and_produce

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