Merge pull request #108353 from Kat-Campise/sql_dw_rename

Sql dw rename

Author: American-Dipper

articles/synapse-analytics/overview-faq.md

@@ -45,7 +45,7 @@ A: Azure Synapse has the following capabilities:
 
 ### Q: How does Azure Synapse Analytics relate to Azure SQL Data Warehouse
 
-A: Azure Synapse Analytics is an evolution of Azure SQL Data Warehouse into an analytics platform. This platform combines data exploration, ingestion, transformation, preparation, and serving analytics layer.
+A: Azure Synapse Analytics is an evolution of Azure SQL Data Warehouse into an analytics platform, which includes SQL pool as the data warehouse solution. This platform combines data exploration, ingestion, transformation, preparation, and serving analytics layer.
 
 ## Use cases
 

articles/synapse-analytics/spark/apache-spark-development-using-notebooks.md

@@ -80,7 +80,7 @@ The following image is an example of how you can write a PySpark query using the
 
 You cannot reference data or variables directly across different languages in a Synapse Studio notebook. In Spark, a temporary table can be referenced across languages. Here is an example of how to read a `Scala` DataFrame in `PySpark` and `SparkSQL` using a Spark temp table as a workaround.
 
-1. In Cell 1, read a DataFrame from SQL DW connector using Scala and create a temporary table.
+1. In Cell 1, read a DataFrame from SQL pool connector using Scala and create a temporary table.
 
    ```scala
    %%scala
@@ -207,7 +207,7 @@ You can specify the timeout duration, the number, and the size of executors to g
 
 ## Bring data to a notebook
 
-You can load data from Azure Blob Storage, Azure Data Lake Store Gen 2, and SQL Data Warehouse as shown in the code samples below.
+You can load data from Azure Blob Storage, Azure Data Lake Store Gen 2, and SQL pool as shown in the code samples below.
 
 ### Read a CSV from Azure Data Lake Store Gen2 as a Spark DataFrame
 
@@ -252,7 +252,7 @@ df = spark.read.option("header", "true") \
 
 ### Read data from the primary storage account
 
-You can access data in the primary storage account directly. There's no need to provide the secret keys. In Data Explorer, right-click on a file and select **New notebook** to see a new notebook with data extractor auto-generated.
+You can access data in the primary storage account directly. There's no need to provide the secret keys. In Data Explorer, right-click on a file and select **New notebook** to see a new notebook with data extractor autogenerated.
 
 ![data-to-cell](./media/apache-spark-development-using-notebooks/synapse-data-to-cell.png)
 
@@ -309,7 +309,7 @@ displayHTML(html)
 
 ## Save notebooks
 
-You have the option to save a single notebook or all notebooks in your workspace.
+You can save a single notebook or all notebooks in your workspace.
 
 1. To save changes you made to a single notebook, select the **Publish** button on the notebook command bar.
 

articles/synapse-analytics/sql-analytics/data-loading-best-practices.md

@@ -59,7 +59,8 @@ Run loads under static rather than dynamic resource classes. Using the static re
 
 ## Allowing multiple users to load
 
-There is often a need to have multiple users load data into a data warehouse. Loading with the [CREATE TABLE AS SELECT (Transact-SQL)](/sql/t-sql/statements/create-table-as-select-azure-sql-data-warehouse) requires CONTROL permissions of the database.  The CONTROL permission gives control access to all schemas. You might not want all loading users to have control access on all schemas. To limit permissions, use the DENY CONTROL statement.
+There is often a need to have multiple users load data into a data warehouse. Loading with the [CREATE TABLE AS SELECT (Transact-SQL)](https://docs.microsoft.com/sql/t-sql/statements/create-table-as-select-azure-sql-data-warehouse?view=aps-pdw-2016-au7
+) requires CONTROL permissions of the database.  The CONTROL permission gives control access to all schemas. You might not want all loading users to have control access on all schemas. To limit permissions, use the DENY CONTROL statement.
 
 For example, consider database schemas, schema_A for dept A, and schema_B for dept B. Let database users user_A and user_B be users for PolyBase loading in dept A and B, respectively. They both have been granted CONTROL database permissions. The creators of schema A and B now lock down their schemas using DENY:
 
@@ -84,7 +85,7 @@ Columnstore indexes require large amounts of memory to compress data into high-q
 - Load enough rows to completely fill new rowgroups. During a bulk load, every 1,048,576 rows get compressed directly into the columnstore as a full rowgroup. Loads with fewer than 102,400 rows send the rows to the deltastore where rows are held in a b-tree index. If you load too few rows, they might all go to the deltastore and not get compressed immediately into columnstore format.
 
 ## Increase batch size when using SQLBulkCopy API or BCP
-As mentioned before, loading with PolyBase will provide the highest throughput with SQL Data Warehouse. If you cannot use PolyBase to load and must use the SQLBulkCopy API (or BCP) you should consider increasing batch size for better throughput - a good rule of thumb is a batch size between 100K to 1M rows.
+As mentioned before, loading with PolyBase will provide the highest throughput with Synapse SQL pool. If you cannot use PolyBase to load and must use the SQLBulkCopy API (or BCP) you should consider increasing batch size for better throughput - a good rule of thumb is a batch size between 100K to 1M rows.
 
 ## Handling loading failures
 
@@ -94,13 +95,13 @@ To fix the dirty records, ensure that your external table and external file form
 
 ## Inserting data into a production table
 
-A one-time load to a small table with an [INSERT statement](/sql/t-sql/statements/insert-transact-sql), or even a periodic reload of a look-up might perform good enough with a statement like `INSERT INTO MyLookup VALUES (1, 'Type 1')`.  However, singleton inserts are not as efficient as performing a bulk load. 
+A one-time load to a small table with an [INSERT statement](https://docs.microsoft.com/sql/t-sql/statements/insert-transact-sql?view=sql-server-ver15), or even a periodic reload of a look-up might perform good enough with a statement like `INSERT INTO MyLookup VALUES (1, 'Type 1')`.  However, singleton inserts are not as efficient as performing a bulk load. 
 
 If you have thousands or more single inserts throughout the day, batch the inserts so you can bulk load them.  Develop your processes to append the single inserts to a file, and then create another process that periodically loads the file.
 
 ## Creating statistics after the load
 
-To improve query performance, it's important to create statistics on all columns of all tables after the first load, or substantial changes occur in the data.  This can be done manually or you can enable [auto-create statistics](https://docs.microsoft.com/azure/sql-data-warehouse/sql-data-warehouse-tables-statistics#automatic-creation-of-statistic).
+To improve query performance, it's important to create statistics on all columns of all tables after the first load, or substantial changes occur in the data.  This can be done manually or you can enable [auto-create statistics](../sql-data-warehouse/sql-data-warehouse-tables-statistics.md?toc=/azure/synapse-analytics/toc.json&bc=/azure/synapse-analytics/breadcrumb/toc.json).
 
 For a detailed explanation of statistics, see [Statistics](development-tables-statistics.md). The following example shows how to manually create statistics on five columns of the Customer_Speed table.
 
@@ -118,7 +119,7 @@ It is good security practice to change the access key to your blob storage on a
 
 To rotate Azure Storage account keys:
 
-For each storage account whose key has changed, issue [ALTER DATABASE SCOPED CREDENTIAL](/sql/t-sql/statements/alter-database-scoped-credential-transact-sql).
+For each storage account whose key has changed, issue [ALTER DATABASE SCOPED CREDENTIAL](https://docs.microsoft.com/sql/t-sql/statements/alter-database-scoped-credential-transact-sql?view=azure-sqldw-latest).
 
 Example: