Updated ODBC article for content perf

davidpeterh · davidpeterh · commit cfa1d5e2cf89 · 2021-04-21T17:16:46.000-04:00
diff --git a/.openpublishing.redirection.json b/.openpublishing.redirection.json
@@ -42945,6 +42945,11 @@
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diff --git a/docs/machine-learning/data-exploration/save-and-load-r-objects-from-sql-server-using-odbc.md b/docs/machine-learning/data-exploration/save-and-load-r-objects-from-sql-server-using-odbc.md
@@ -4,21 +4,21 @@ description: The RevoScaleR package includes serialization and deserialization f
 ms.prod: sql
 ms.technology: machine-learning-services
 
-ms.date: 04/15/2018  
+ms.date: 04/21/2020
 ms.topic: how-to
 author: dphansen
 ms.author: davidph
-ms.custom: seo-lt-2019
+ms.custom: contperf-fy21q4
 monikerRange: ">=sql-server-2016||>=sql-server-linux-ver15"
 ---
-# Save and load R objects from SQL Server using ODBC
+# Use ODBC to save and load R objects in SQL Server Machine Learning Services
 [!INCLUDE [SQL Server 2016 and later](../../includes/applies-to-version/sqlserver2016.md)]
 
-SQL Server R Services can store serialized R objects in a table and then load the object from the table as needed, without you having to re-run the R code or retrain the model. This ability to save R objects in a database is critical for scenarios such as training and saving a model, and then using it later for scoring or analysis.
+Learn how to use the **RevoScaleR** package to store serialized R objects in a table and then load the object from the table as needed with [SQL Server Machine Learning Services](../sql-server-machine-learning-services.md). This can be used when training and saving a model, and then use it later for scoring or analysis.
 
-To improve performance of this critical step, the **RevoScaleR** package now includes new serialization and deserialization functions that greatly improve performance, and store the object more compactly. This article describes these functions and how to use them.
+To improve performance, the **RevoScaleR** package now includes new serialization and deserialization functions that improve performance and store the object more compactly. 
 
-## Overview
+## RevoScaleR package
 
 The **RevoScaleR** package now includes new functions that make it easier to save R objects to SQL Server and then read the objects from the SQL Server table. In general, each function call uses a simple key value store, in which the key is the name of the object, and the value associated with the key is the varbinary R object to be moved in or out of a table.
 
@@ -40,7 +40,7 @@ By default, any object that you call from R to move to SQL Server is serialized
 
 - `rxListKeys` lists as key-value pairs all the available objects. This helps you determine the names and versions of the R objects.
 
-For detailed help on the syntax of each function, use R help. Details are also available in the [ScaleR reference](/r-server/r-reference/revoscaler/revoscaler).
+For detailed help on the syntax of each function, use R help. Details are also available in the [ScaleR reference](/machine-learning-server/r-reference/revoscaler/revoscaler).
 
 ## How to store R objects in SQL Server using ODBC
 
@@ -109,4 +109,8 @@ This procedure demonstrates how you can use the new functions to load a model fr
 
    ```R
     infertLogit2 <- rxReadObject(ds, "logit.model")
-   ```
+   ```
+
+## Next steps
+
++ [What is SQL Server Machine Learning Services?](../sql-server-machine-learning-services.md)
diff --git a/docs/machine-learning/toc.yml b/docs/machine-learning/toc.yml
@@ -247,7 +247,7 @@ items:
     - name: R
       items:
       - name: Load R objects using ODBC
-        href: ../machine-learning/r/save-and-load-r-objects-from-sql-server-using-odbc.md
+        href: ../machine-learning/data-exploration/save-and-load-r-objects-from-sql-server-using-odbc.md
       - name: Predictive modeling with R
         href: ../machine-learning/r/data-exploration-and-predictive-modeling-with-r.md
       - name: Create multiple models using rxExecBy
