20230106 what's new update

Author: WilliamDAssafMSFT

articles/synapse-analytics/whats-new-archive.md

@@ -185,16 +185,17 @@ What follows are the previous format of monthly news updates for Synapse Analyti
 
 ## June 2022 update
 
-## General
+### General
 
 * **Azure Orbital analytics with Synapse Analytics** - We now offer an [Azure Orbital analytics sample solution](https://github.com/Azure/Azure-Orbital-Analytics-Samples) showing an end-to-end implementation of extracting, loading, transforming, and analyzing spaceborne data by using geospatial libraries and AI models with [Azure Synapse Analytics](overview-what-is.md). The sample solution also demonstrates how to integrate geospatial-specific [Azure Cognitive Services](../cognitive-services/index.yml) models, AI models from partners, and bring-your-own-data models.
 
 * **Azure Synapse success by design** - Project success is no accident and requires careful planning and execution. The Synapse Analytics' Success by Design playbooks are now available. The [Azure Synapse proof of concept playbook](./guidance/proof-of-concept-playbook-overview.md) provides a guide to scope, design, execute, and evaluate a proof of concept for SQL or Spark workloads. These guides contain best practices from the most challenging and complex solution implementations incorporating Azure Synapse. To learn more about the Azure Synapse proof of concept playbook, read [Success by Design](./guidance/success-by-design-introduction.md).
-## SQL
+
+### SQL
 
 **Result set size limit increase** - We know that you turn to Azure Synapse Analytics to work with large amounts of data. With that in mind, the maximum size of query result sets in Serverless SQL pools has been increased from 200 GB to 400 GB. This limit is shared between concurrent queries. To learn more about this size limit increase and other constraints, read [Self-help for serverless SQL pool](./sql/resources-self-help-sql-on-demand.md?tabs=x80070002#constraints).
 
-## Synapse data explorer
+### Synapse data explorer
 
 * **Web Explorer new homepage** - The new Synapse Web Explorer homepage makes it even easier to get started with Synapse Web Explorer. The [Web Explorer homepage](https://dataexplorer.azure.com/home) now includes the following sections:
 
@@ -208,7 +209,7 @@ What follows are the previous format of monthly news updates for Synapse Analyti
 
 * **Time Zone settings for Web Explorer** - Being able to display data in different time zones is very powerful. You can now decide to view the data in UTC time, your local time zone, or the time zone of the monitored device/machine. The Time Zone settings of the Web Explorer now apply to both the Query results and to the Dashboard. By changing the time zone, the dashboards will be automatically refreshed to present the data with the selected time zone.  For more information on time zone settings, read [Change datetime to specific time zone](/azure/data-explorer/web-query-data#change-datetime-to-specific-time-zone).
 
-## Data integration
+### Data integration
 
 * **Fuzzy Join option in Join Transformation** - Fuzzy matching with a sliding similarity score option has been added to the Join transformation in Mapping Data Flows. You can create inner and outer joins on data values that are similar rather than exact matches! Previously, you would have had to use an exact match. The sliding scale value goes from 60% to 100%, making it easy to adjust the similarity threshold of the match. For learn more about fuzzy joins, read [Join transformation in mapping data flow](../data-factory/data-flow-join.md).
 
@@ -218,7 +219,7 @@ What follows are the previous format of monthly news updates for Synapse Analyti
 
 * **User Defined Functions [Generally Available]** - We're excited to announce that user defined functions (UDFs) are now Generally Available. With user-defined functions, you can create customized expressions that can be reused across multiple mapping data flows. You no longer have to use the same string manipulation, math calculations, or other complex logic several times. User-defined functions will be grouped in libraries to help developers group common sets of functions.  To learn more about user defined functions, read [User defined functions in mapping data flows](https://techcommunity.microsoft.com/t5/azure-data-factory-blog/introducing-user-defined-functions-preview-for-mapping-data/ba-p/3414628).
 
-## Machine learning
+### Machine learning
 
 **Distributed Deep Neural Network Training with Horovod and Petastorm [Public Preview]** - To simplify the process for creating and managing GPU-accelerated pools, Azure Synapse takes care of pre-installing low-level libraries and setting up all the complex networking requirements between compute nodes. This integration allows users to get started with GPU- accelerated pools within just a few minutes.