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Author: alexbuckgit

articles/stream-analytics/power-bi-output.md

@@ -48,26 +48,26 @@ Azure Stream Analytics updates the data model dynamically at runtime when the ou
 
 This table covers the data type conversions from [Stream Analytics data types](/stream-analytics-query/data-types-azure-stream-analytics) to Power BI [Entity Data Model (EDM) types](/dotnet/framework/data/adonet/entity-data-model), if a Power BI dataset and table don't exist.
 
-From Stream Analytics | To Power BI
------|-----
-bigint | Int64
-nvarchar(max) | String
-datetime | Datetime
-float | Double
-Record array | String type, constant value `IRecord` or `IArray`
+| From Stream Analytics | To Power BI |
+| -----|----- |
+| bigint | Int64 |
+| nvarchar(max) | String |
+| datetime | Datetime |
+| float | Double |
+| Record array | String type, constant value `IRecord` or `IArray` |
 
 ### Update the schema
 
 Stream Analytics infers the data model schema based on the first set of events in the output. Later, if necessary, the data model schema is updated to accommodate incoming events that might not fit into the original schema.
 
 Avoid the `SELECT *` query to prevent dynamic schema update across rows. In addition to potential performance implications, it might result in uncertainty of the time taken for the results. Select the exact fields that need to be shown on the Power BI dashboard. Additionally, the data values should be compliant with the chosen data type.
 
-Previous/current | Int64 | String | Datetime | Double
------------------|-------|--------|----------|-------
-Int64 | Int64 | String | String | Double
-Double | Double | String | String | Double
-String | String | String | String | String 
-Datetime | String | String |  Datetime | String
+| Previous/current | Int64 | String | Datetime | Double |
+| ---|---|---|---|--- |
+| Int64 | Int64 | String | String | Double |
+| Double | Double | String | String | Double |
+| String | String | String | String | String  |
+| Datetime | String | String |  Datetime | String |
 
 ## Limitations and best practices
 Currently, Power BI can be called roughly once per second. Streaming visuals support packets of 15 KB. Beyond that, streaming visuals fail (but push continues to work). Because of these limitations, Power BI lends itself most naturally to cases where Azure Stream Analytics does a significant data load reduction. We recommend using a Tumbling window or Hopping window to ensure that data push is at most one push per second, and that your query lands within the throughput requirements. For more info on output batch size, see [Power BI REST API limits](/power-bi/developer/automation/api-rest-api-limitations).