20240719 freshness pass

Author: WilliamDAssafMSFT

articles/synapse-analytics/index.yml

@@ -11,7 +11,7 @@ metadata:
 
   author: WilliamDAssafMSFT
   ms.author: wiassaf
-  ms.date: 08/09/2022
+  ms.date: 07/19/2024
 
 # linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new
 

articles/synapse-analytics/sql-data-warehouse/media/sql-data-warehouse-overview-what-is/data-warehouse-solution.png

@@ -3,7 +3,7 @@ title: What is dedicated SQL pool (formerly SQL DW)?
 description: Dedicated SQL pool (formerly SQL DW) in Azure Synapse Analytics is the enterprise data warehousing functionality in Azure Synapse Analytics.
 author: WilliamDAssafMSFT
 ms.author: wiassaf
-ms.date: 02/21/2023
+ms.date: 07/19/2024
 ms.service: synapse-analytics
 ms.subservice: sql-dw
 ms.topic: overview
@@ -13,11 +13,7 @@ ms.topic: overview
 
 Azure Synapse Analytics is an analytics service that brings together enterprise data warehousing and Big Data analytics. Dedicated SQL pool (formerly SQL DW) refers to the enterprise data warehousing features that are available in Azure Synapse Analytics.
 
-
-
-![Dedicated SQL pool (formerly SQL DW) in relation to Azure Synapse](./media/sql-data-warehouse-overview-what-is/dedicated-sql-pool.png)
-
-
+:::image type="content" source="media/sql-data-warehouse-overview-what-is/dedicated-sql-pool.png" alt-text="Diagram of dedicated SQL pool (formerly SQL DW) in relation to Azure Synapse." lightbox="media/sql-data-warehouse-overview-what-is/dedicated-sql-pool.png":::
 
 Dedicated SQL pool (formerly SQL DW) represents a collection of analytic resources that are provisioned when using Synapse SQL. The size of a dedicated SQL pool (formerly SQL DW) is determined by Data Warehousing Units (DWU).
 
@@ -30,15 +26,15 @@ Once your dedicated SQL pool is created, you can import big data with simple [Po
 
 Data warehousing is a key component of a cloud-based, end-to-end big data solution.
 
-![Data warehouse solution](./media/sql-data-warehouse-overview-what-is/data-warehouse-solution.png)
+:::image type="content" source="media/sql-data-warehouse-overview-what-is/data-warehouse-solution.png" alt-text="Diagram of data warehouse solutions featuring zones for Ingest, Store, Prep & Train, and Model & Serve." lightbox="media/sql-data-warehouse-overview-what-is/data-warehouse-solution.png":::
 
 In a cloud data solution, data is ingested into big data stores from a variety of sources. Once in a big data store, Hadoop, Spark, and machine learning algorithms prepare and train the data. When the data is ready for complex analysis, dedicated SQL pool uses PolyBase to query the big data stores. PolyBase uses standard T-SQL queries to bring the data into dedicated SQL pool (formerly SQL DW) tables.
 
 Dedicated SQL pool (formerly SQL DW) stores data in relational tables with columnar storage. This format significantly reduces the data storage costs, and improves query performance. Once data is stored, you can run analytics at massive scale. Compared to traditional database systems, analysis queries finish in seconds instead of minutes, or hours instead of days.
 
 The analysis results can go to worldwide reporting databases or applications. Business analysts can then gain insights to make well-informed business decisions.
 
-## Next steps
+## Related content
 
 - Explore [Azure Synapse architecture](massively-parallel-processing-mpp-architecture.md)
 - Quickly [create a dedicated SQL pool](../quickstart-create-sql-pool-studio.md)
@@ -52,5 +48,5 @@ Or look at some of these other Azure Synapse resources:
 - Search [Blogs](https://azure.microsoft.com/blog/tag/azure-sql-data-warehouse/)
 - Submit a [Feature requests](https://feedback.azure.com/d365community/forum/9b9ba8e4-0825-ec11-b6e6-000d3a4f07b8)
 - [Create a support ticket](sql-data-warehouse-get-started-create-support-ticket.md)
-- Search [Microsoft Q&A question page](/answers/topics/azure-synapse-analytics.html)
-- Search [Stack Overflow forum](https://stackoverflow.com/questions/tagged/azure-sqldw)
+- [Microsoft Q&A question page](/answers/topics/azure-synapse-analytics.html)
+- [Stack Overflow forum](https://stackoverflow.com/questions/tagged/azure-sqldw)

articles/synapse-analytics/sql-data-warehouse/media/sql-data-warehouse-overview-what-is/dedicated-sql-pool.png

@@ -1,14 +1,15 @@
 ---
 title: Distributed tables design guidance
 description: Recommendations for designing hash-distributed and round-robin distributed tables using dedicated SQL pool.
-ms.service: synapse-analytics
-ms.topic: conceptual
-ms.subservice: sql-dw 
-ms.date: 03/20/2023
 author: WilliamDAssafMSFT
 ms.author: wiassaf
 ms.reviewer: mariyaali
-ms.custom: azure-synapse
+ms.date: 07/19/2024
+ms.service: synapse-analytics
+ms.subservice: sql-dw
+ms.topic: conceptual
+ms.custom:
+  - azure-synapse
 ---
 
 # Guidance for designing distributed tables using dedicated SQL pool in Azure Synapse Analytics
@@ -35,7 +36,7 @@ As part of table design, understand as much as possible about your data and how
 
 A hash-distributed table distributes table rows across the Compute nodes by using a deterministic hash function to assign each row to one [distribution](massively-parallel-processing-mpp-architecture.md#distributions).
 
-:::image type="content" source="./media/sql-data-warehouse-tables-distribute/hash-distributed-table.png" alt-text="Distributed table" lightbox="./media/sql-data-warehouse-tables-distribute/hash-distributed-table.png":::
+:::image type="content" source="media/sql-data-warehouse-tables-distribute/hash-distributed-table.png" alt-text="Diagram of a distributed table.":::
 
 Since identical values always hash to the same distribution, SQL Analytics has built-in knowledge of the row locations. In dedicated SQL pool this knowledge is used to minimize data movement during queries, which improves query performance.
 
@@ -121,7 +122,7 @@ For best performance, all of the distributions should have approximately the sam
 
 To balance the parallel processing, select a distribution column or set of columns that:
 
-- **Has many unique values.** The distribution column(s) can have duplicate values.  All rows with the same value are assigned to the same distribution. Since there are 60 distributions, some distributions can have > 1 unique values while others may end with zero values.  
+- **Has many unique values.** The distribution column(s) can have duplicate values.  All rows with the same value are assigned to the same distribution. Since there are 60 distributions, some distributions can have > 1 unique values while others can end with zero values.  
 - **Does not have NULLs, or has only a few NULLs.** For an extreme example, if all values in the distribution column(s) are NULL, all the rows are assigned to the same distribution. As a result, query processing is skewed to one distribution, and does not benefit from parallel processing.
 - **Is not a date column**. All data for the same date lands in the same distribution, or will cluster records by date. If several users are all filtering on the same date (such as today's date), then only 1 of the 60 distributions do all the processing work.
 
@@ -153,7 +154,7 @@ DBCC PDW_SHOWSPACEUSED('dbo.FactInternetSales');
 To identify which tables have more than 10% data skew:
 
 1. Create the view `dbo.vTableSizes` that is shown in the [Tables overview](sql-data-warehouse-tables-overview.md#table-size-queries) article.  
-2. Run the following query:
+1. Run the following query:
 
 ```sql
 select *
@@ -178,7 +179,7 @@ To avoid data movement during a join:
 - The tables involved in the join must be hash distributed on **one** of the columns participating in the join.
 - The data types of the join columns must match between both tables.
 - The columns must be joined with an equals operator.
-- The join type may not be a `CROSS JOIN`.
+- The join type cannot be a `CROSS JOIN`.
 
 To see if queries are experiencing data movement, you can look at the query plan.  
 
@@ -233,8 +234,7 @@ RENAME OBJECT [dbo].[FactInternetSales] TO [FactInternetSales_ProductKey];
 RENAME OBJECT [dbo].[FactInternetSales_CustomerKey] TO [FactInternetSales];
 ```
 
-## Next steps
-
+## Related content
 To create a distributed table, use one of these statements:
 
 - [CREATE TABLE (dedicated SQL pool)](/sql/t-sql/statements/create-table-azure-sql-data-warehouse?toc=/azure/synapse-analytics/sql-data-warehouse/toc.json&bc=/azure/synapse-analytics/sql-data-warehouse/breadcrumb/toc.json&view=azure-sqldw-latest&preserve-view=true)