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Create a Streaming Insight Using Builder

Use near real-time data in Data 360 by creating a streaming insight. A streaming insight focuses on data at a specific time. You can write SQL expressions to compute streaming metrics across dimensions from your real-time data sources. Use a streaming insight to perform cross-functional orchestration and optimize your data in Data 360.

Required Editions

Available in: All Editions supported by Data 360. See Data 360 edition availability.
User Permission Sets Needed
To create streaming insights:

Permission set:

  • Data Cloud Architect

Setting up streaming insights requires several prerequisites and steps. To ensure the best results, follow this action flow.

streaming insights data flow
  • Data sources—Map sources to different objects from Web & Mobile SDK and Marketing Cloud Personalization (formerly Interaction Studio) data streams.
  • Identity resolution and data mapping—Ingest your data into Data 360, and create unified individuals with identity resolution.
  • Insights—Streaming Insights are similar to calculated insights but have specialized functions to manage streaming data.
  • Match rules—Enrich with unified individual data from customers.
  • Enrichment—Enhance data actions with profile-related attributes.
  • Data actions—Apply data actions on a streaming insight and evaluate if the action is necessary.
  1. In Data Cloud, go to the Calculated Insights tab, click New.
  2. From the Data Space dropdown, select a data space.
    You can use only the data spaces that you have access to.
  3. Click Streaming Insight.
  4. Click Use Visual Builder and click Next.
  5. Select the object, and then click Next.
    Only the objects that are created from streaming data sources such as Web SDK and Mobile SDK are available to create a streaming insight.
  6. If your Insight includes currency fields, select the Insight Currency value at the top of the page.
  7. Add the nodes by clicking + next to the object.
    You must select at least one aggregate node.
    Streaming Insight Nodes
  8. Add measures and dimensions to your insight by clicking Aggregate.
    You must select at least one measure.
    1. Enter a date and time window duration for your insight.
    2. From the Granularity dropdown, select a time interval.
    3. Under Measures, click +.
    4. Select a metric function and the field that you want to calculate, and then click Next.
    5. Enter the metric name, and click Apply.
    6. Under Dimensions, click +.
    7. Select the field that you want to group by, and click Next.
    8. Enter the dimension name, and click Apply.
  9. To save the aggregate node, click Apply.
  10. (Optional) To enhance your insight with additional data, add the join and filters nodes.
  11. Click Save and Run.
  12. Enter the streaming insight name, and click Next.
    The Streaming Insight API Name field is auto-filled.
  13. Click Save.

You can now view your streaming insight on the record home page. The last run status of a streaming insight is always Processing.

Example
Example 
SELECT COUNT( RealTimeMobileEvents__dlm.pageviews__c ) as page_views__c,
ssot__Individual__dlm.ssot__Id__c as customer_id__c,
RealTimeMobileEvents__dlm.product__c as product__c,
WINDOW.START as start__c,
WINDOW.END as end__c
FROM 
RealTimeMobileEvents__dlm 
JOIN
 ssot__Individual__dlm 
ON 
ssot__Individual__dlm.ssot__Id__c = RealTimeMobileEvents__dlm.deviceId__c 
GROUP BY
window( RealTimeMobileEvents__dlm.dateTime__c ,'5 MINUTE'),customer_id__c, product__c
SQL Result
start_c end_c customer_id_c product_c page_views_c
2023-01-01 12.00 AM 2023-01-01 12.05 AM 1 HK0012 1
2023-01-01 12.05 AM 2023-01-01 12.10 AM 2 JK0078 2
2023-01-01 12.10 AM 2023-01-01 12.15 AM 3 HK0078 1

After you create a streaming insight, validate it in Data Explorer.

See Also