renaming SQL Analytics to Synapse SQL

Author: julieMSFT

articles/synapse-analytics/metadata/database.md

@@ -91,5 +91,5 @@ Verify the schema for the newly created database in the results.
 - [Learn more about Azure Synapse Analytics' shared metadata](overview.md)
 - [Learn more about Azure Synapse Analytics' shared metadata Tables](table.md)
 
-<!-- - [Learn more about the Synchronization with SQL Analytics on-demand](overview.md)
-- [Learn more about the Synchronization with SQL Analytics pools](overview.md)-->
+<!-- - [Learn more about the Synchronization with SQL on-demand](overview.md)
+- [Learn more about the Synchronization with SQL pools](overview.md)-->

articles/synapse-analytics/overview-cheat-sheet.md

@@ -26,7 +26,7 @@ The Azure Synapse Analytics cheat sheet will guide you through the basic concept
 | Nouns and verbs                         | What it does       |
 |:---                                 |:---                 |
 | **Synapse Workspace (preview)** | A securable collaboration boundary for doing cloud-based enterprise analytics in Azure. A workspace is deployed in a specific region and has an associated ADLS Gen2 account and file system (for storing temporary data). A workspace is under a resource group. |
-| **SQL Analytics**   | Run analytics with pools or with on-demand capabilities.  |
+| **Synapse SQL**   | Run analytics with pools or with on-demand capabilities.  |
 | **SQL pool**   | 0-to-N SQL provisioned resources with their corresponding databases can be deployed in a workspace. Each SQL pool has an associated database. A SQL pool can be scaled, paused and resumed manually or automatically. A SQL pool can scale from 100 DWU up to 30,000 DWU.       |
 | **SQL on-demand (preview)**   | Distributed data processing system built for large-scale data that lets you run T-SQL queries over data in data lake. It is serverless so you don't need to manage infrastructure.       |
 |**Apache Spark** | Spark run-time used in a Spark pool. The current version supported is Spark 2.4 with Python 3.6.1, Scala 2.11.12, .NET support for Apache Spark 0.5 and Delta Lake 0.3.  | 

articles/synapse-analytics/sql-data-warehouse/design-elt-data-loading.md

@@ -63,7 +63,7 @@ Tools and services you can use to move data to Azure Storage:
 
 - [Azure ExpressRoute](../../expressroute/expressroute-introduction.md?toc=/azure/synapse-analytics/sql-data-warehouse/toc.json&bc=/azure/synapse-analytics/sql-data-warehouse/breadcrumb/toc.json) service enhances network throughput, performance, and predictability. ExpressRoute is a service that routes your data through a dedicated private connection to Azure. ExpressRoute connections do not route data through the public internet. The connections offer more reliability, faster speeds, lower latencies, and higher security than typical connections over the public internet.
 - [AZCopy utility](../../storage/common/storage-choose-data-transfer-solution.md?toc=/azure/synapse-analytics/sql-data-warehouse/toc.json&bc=/azure/synapse-analytics/sql-data-warehouse/breadcrumb/toc.json) moves data to Azure Storage over the public internet. This works if your data sizes are less than 10 TB. To perform loads on a regular basis with AZCopy, test the network speed to see if it is acceptable.
-- [Azure Data Factory (ADF)](../../data-factory/introduction.md?toc=/azure/synapse-analytics/sql-data-warehouse/toc.json&bc=/azure/synapse-analytics/sql-data-warehouse/breadcrumb/toc.json) has a gateway that you can install on your local server. Then you can create a pipeline to move data from your local server up to Azure Storage. To use Data Factory with SQL Analytics, see [Loading data for SQL Analytics](../../data-factory/load-azure-sql-data-warehouse.md?toc=/azure/synapse-analytics/sql-data-warehouse/toc.json&bc=/azure/synapse-analytics/sql-data-warehouse/breadcrumb/toc.json).
+- [Azure Data Factory (ADF)](../../data-factory/introduction.md?toc=/azure/synapse-analytics/sql-data-warehouse/toc.json&bc=/azure/synapse-analytics/sql-data-warehouse/breadcrumb/toc.json) has a gateway that you can install on your local server. Then you can create a pipeline to move data from your local server up to Azure Storage. To use Data Factory with SQL pool, see [Loading data for SQL pool](../../data-factory/load-azure-sql-data-warehouse.md?toc=/azure/synapse-analytics/sql-data-warehouse/toc.json&bc=/azure/synapse-analytics/sql-data-warehouse/breadcrumb/toc.json).
 
 ## 3. Prepare the data for loading