fixed warning, toc and index

Author: julieMSFT

articles/synapse-analytics/sql-data-warehouse/breadcrumb/toc.yml

@@ -0,0 +1,33 @@
+- name: Azure
+  tocHref: /azure/
+  topicHref: /azure/index
+  items:
+  - name: Synapse Analytics
+    tocHref: /azure/sql-database/
+    topicHref: /azure/sql-data-warehouse/index
+
+- name: Azure
+  tocHref: /azure/
+  topicHref: /azure/index
+  items:
+  - name: Synapse Analytics
+    tocHref: /azure/azure-databricks/
+    topicHref: /azure/sql-data-warehouse/index
+
+- name: Azure
+  tocHref: /azure/
+  topicHref: /azure/index
+  items:
+  - name: Synapse Analytics
+    tocHref: /azure/data-factory/
+    topicHref: /azure/sql-data-warehouse/index
+
+- name: Azure
+  tocHref: /azure/
+  topicHref: /azure/index
+  items:
+  - name: Synapse Analytics
+    tocHref: /sql/t-sql/
+    topicHref: /azure/sql-data-warehouse/index
+
+

articles/synapse-analytics/sql-data-warehouse/index.yml

@@ -0,0 +1,124 @@
+### YamlMime:Landing
+
+title: Azure Synapse Analytics (formerly Azure SQL Data Warehouse)  # < 60 chars
+summary: Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. # < 160 chars
+metadata:
+  title: Azure Synapse Analytics # Required; page title displayed in search results. Include the brand. < 60 chars.
+  description: Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. # Required; article description that is displayed in search results. < 160 chars.
+  services: sql-data-warehouse
+  ms.service: sql-data-warehouse #Required; service per approved list. service slug assigned to your service by ACOM.
+  ms.subservice: design
+  ms.topic: landing-page # Required
+  ms.collection: collection
+  author: julieMSFT #Required; your GitHub user alias, with correct capitalization.
+  ms.author: jrasnick #Required; microsoft alias of author; optional team alias.
+  ms.date: 10/03/2019 #Required; mm/dd/yyyy format.
+
+# linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new
+
+landingContent:
+# Cards and links should be based on top customer tasks or top subjects
+# Start card title with a verb
+  # Card (optional)
+  - title: About Azure Synapse Analytics 
+    linkLists:
+      - linkListType: overview
+        links:
+          - text: What is Azure Synapse?
+            url: sql-data-warehouse-overview-what-is.md
+      - linkListType: architecture
+        links:
+          - text: Azure Synapse architecture
+            url: massively-parallel-processing-mpp-architecture.md
+          - text: Tips and best practices
+            url: cheat-sheet.md
+          - text: Reference Architecture
+            url: https://docs.microsoft.com/azure/architecture/reference-architectures/data/enterprise-bi-synapse
+
+  # Card
+  - title: Getting started
+    linkLists:
+      - linkListType: deploy
+        links:
+          - text: Create a SQL pool (data warehouse)
+            url: create-data-warehouse-portal.md
+  #         # - text: linktext2
+  #         #   url: file2.md
+
+  # Card (optional)
+  - title: Load data
+    linkLists:
+      - linkListType: concept
+        links:
+          - text: Design data loading strategy
+            url: design-elt-data-loading.md
+          - text: Best practices
+            url: guidance-for-loading-data.md
+      - linkListType: how-to-guide
+        links:
+          - text: Load data from Azure Data Lake Storage
+            url: sql-data-warehouse-load-from-azure-data-lake-store.md
+      - linkListType: tutorial
+        links:
+          - text: Load data from Azure Blob storage
+            url: load-data-from-azure-blob-storage-using-polybase.md
+
+  # Card
+  - title: Performance tuning
+    linkLists:
+      - linkListType: overview
+        links:
+          - text: Best practices
+            url: sql-data-warehouse-best-practices.md
+          - text: Ordered clustered columnstore index tuning
+            url: performance-tuning-ordered-cci.md
+          - text: Use materialized views for workload tuning
+            url: performance-tuning-materialized-views.md
+      - linkListType: how-to-guide
+        links:
+          - text: Analyze your workload
+            url: analyze-your-workload.md
+          # - text: linktext2
+          #   url: file2.md
+
+  # Card
+  - title: Manage and monitor
+    linkLists:
+      - linkListType: overview
+        links:
+          - text: Learn to manage and monitor your data warehouse
+            url: sql-data-warehouse-overview-manageability-monitoring.md
+      #     - text: linktext2
+      #       url: file2.md
+      - linkListType: how-to-guide
+        links:
+          - text: Monitor your workload using DMVs
+            url: sql-data-warehouse-manage-monitor.md
+          - text: Manage and monitor workload importance
+            url: sql-data-warehouse-how-to-manage-and-monitor-workload-importance.md
+
+  # Card
+  - title: Secure your data warehouse
+    linkLists:
+      - linkListType: overview
+        links:
+          - text: Understand the basics of securing your data warehouse
+            url: sql-data-warehouse-overview-manage-security.md
+          # - text: linktext2
+          #   url: file2.md
+      - linkListType: how-to-guide
+        links:
+          - text: Configure Azure Active Directory authentication
+            url: /azure/sql-database/sql-database-aad-authentication-configure?toc=/azure/sql-data-warehouse/toc.json&bc=/azure/sql-data-warehouse/breadcrumb/toc.json
+      #     - text: linktext2
+      #       url: file2.md
+
+  # Card
+  - title: Resources
+    linkLists:
+      - linkListType: video
+        links:
+          - text: Watch the latest data warehouse videos
+            url:  sql-data-warehouse-videos
+  #         # - text: linktext2
+  #         #   url: file2.md

articles/synapse-analytics/sql-data-warehouse/sql-data-warehouse-best-practices-development.md

@@ -49,7 +49,7 @@ See also [Understanding transactions](sql-data-warehouse-develop-transactions.md
 ## Use the smallest possible column size
 When defining your DDL, using the smallest data type that will support your data will improve query performance.  This is especially important for CHAR and VARCHAR columns.  If the longest value in a column is 25 characters, then define your column as VARCHAR(25).  Avoid defining all character columns to a large default length.  In addition, define columns as VARCHAR when that is all that is needed rather than use NVARCHAR.
 
-See also [Table overview](sql-data-warehouse-tables-overview.md), [Table data types](sql-data-warehouse-tables-data-types.md), [CREATE TABLE](../../sql-data-warehouse/sql-data-warehouse-tables-overview)
+See also [Table overview](sql-data-warehouse-tables-overview.md), [Table data types](sql-data-warehouse-tables-data-types.md), [CREATE TABLE](sql-data-warehouse-tables-overview.md)
 
 ## Optimize clustered columnstore tables
 Clustered columnstore indexes are one of the most efficient ways you can store your data in SQL pool.  By default, tables in SQL pool are created as Clustered ColumnStore.  To get the best performance for queries on columnstore tables, having good segment quality is important.  When rows are written to columnstore tables under memory pressure, columnstore segment quality may suffer.  Segment quality can be measured by number of rows in a compressed Row Group.  See the [Causes of poor columnstore index quality](sql-data-warehouse-tables-index.md#causes-of-poor-columnstore-index-quality) in the [Table indexes](sql-data-warehouse-tables-index.md) article for step by step instructions on detecting and improving segment quality for clustered columnstore tables.  Because high-quality columnstore segments are important, it's a good idea to use users IDs that are in the medium or large resource class for loading data. Using lower [data warehouse units](what-is-a-data-warehouse-unit-dwu-cdwu.md) means you want to assign a larger resource class to your loading user.

articles/synapse-analytics/sql-data-warehouse/sql-data-warehouse-get-started-connect-sqlcmd.md

@@ -18,7 +18,7 @@ ms.custom: seo-lt-2019
 > * [Power BI](sql-data-warehouse-get-started-visualize-with-power-bi.md)
 > * [Azure Machine Learning](sql-data-warehouse-get-started-analyze-with-azure-machine-learning.md)
 > * [Visual Studio](sql-data-warehouse-query-visual-studio.md)
-> * [sqlcmd](../synapse-analytics/sql-data-warehouse/sql-data-warehouse-get-started-connect-sqlcmd.md) 
+> * [sqlcmd](sql-data-warehouse-get-started-connect-sqlcmd.md) 
 > * [SSMS](sql-data-warehouse-query-ssms.md)
 > 
 > 

articles/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-overview.md

@@ -61,7 +61,7 @@ A temporary table only exists for the duration of the session. You can use a tem
 An external table points to data located in Azure Storage blob or Azure Data Lake Store. When used in conjunction with the CREATE TABLE AS SELECT statement, selecting from an external table imports data into SQL Data Warehouse. External tables are therefore useful for loading data. For a loading tutorial, see [Use PolyBase to load data from Azure blob storage](load-data-from-azure-blob-storage-using-polybase.md).
 
 ## Data types
-SQL Data Warehouse supports the most commonly used data types. For a list of the supported data types, see [data types in CREATE TABLE reference](/sql/t-sql/statements/create-table-azure-sql-data-warehouse#DataTypes) in the CREATE TABLE statement. For guidance on using data types, see [Data types](../synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-data-types.md).
+SQL Data Warehouse supports the most commonly used data types. For a list of the supported data types, see [data types in CREATE TABLE reference](/sql/t-sql/statements/create-table-azure-sql-data-warehouse#DataTypes) in the CREATE TABLE statement. For guidance on using data types, see [Data types](sql-data-warehouse-tables-data-types.md).
 
 ## Distributed tables
 A fundamental feature of SQL Data Warehouse is the way it can store and operate on tables across [distributions](massively-parallel-processing-mpp-architecture.md#distributions).  SQL Data Warehouse supports three methods for distributing data, round-robin (default), hash and replicated.
@@ -100,7 +100,7 @@ ALTER TABLE SalesFact_DailyFinalLoad SWITCH PARTITION 256 TO SalesFact PARTITION
 ## Columnstore indexes
 By default, SQL Data Warehouse stores a table as a clustered columnstore index. This form of data storage achieves high data compression and query performance on large tables.  The clustered columnstore index is usually the best choice, but in some cases a clustered index or a heap is the appropriate storage structure.  A heap table can be especially useful for loading transient data, such as a staging table which is transformed into a final table.
 
-For a list of columnstore features, see [What's new for columnstore indexes](/sql/relational-databases/indexes/columnstore-indexes-what-s-new). To improve columnstore index performance, see [Maximizing rowgroup quality for columnstore indexes](../synapse-analytics/sql-data-warehouse/sql-data-warehouse-memory-optimizations-for-columnstore-compression.md).
+For a list of columnstore features, see [What's new for columnstore indexes](/sql/relational-databases/indexes/columnstore-indexes-what-s-new). To improve columnstore index performance, see [Maximizing rowgroup quality for columnstore indexes](sql-data-warehouse-memory-optimizations-for-columnstore-compression.md).
 
 ## Statistics
 The query optimizer uses column-level statistics when it creates the plan for executing a query. To improve query performance, it's important to have statistics on individual columns, especially columns used in query joins. [Creating statistics](https://docs.microsoft.com/azure/sql-data-warehouse/sql-data-warehouse-tables-statistics#automatic-creation-of-statistic) happens automatically.  However, updating statistics does not happen automatically. Update statistics after a significant number of rows are added or changed. For example, update statistics after a load. For more information, see [Statistics guidance](sql-data-warehouse-tables-statistics.md).