Why we’re (still) excited for Azure Synapse Analytics

Why we’re (still) excited for Azure Synapse Analytics

Azure Synapse Analytics, made generally available by Microsoft December 2020, offers a variety of tools and technologies to accelerate the time to insight when working with big data. These are the four Azure Synapse features that we’re most excited to see businesses use to their advantage.

This is a follow up to our earlier blog, 4 reasons why we’re excited for Azure Synapse Analytics.

Ever since Azure made the Azure SQL Data Warehouse generally available in 2016, there have been various updates and several iterations of the service. In 2019, SQL Data Warehouse was rebranded as Azure Synapse Analytics.

Azure Synapse Analytics overview

Image source: Microsoft

Azure Synapse, since its launch, promised to be a limitless analytics service that brought together enterprise data warehousing and Big Data analytics. Now, after more than a year, the service has been growing, evolving, and pleasantly surprising the entire data community.

Azure Synapse will also be part of Microsoft’s push for an Intelligent Data Platform (announced by Satya at Build 2022.) This means it will be even easier to integrate with other services in the Intelligent Data Platform including SQL Server, Azure SQL, Azure Cosmos DB, Power BI, Microsoft Purview, and Azure AI.

So, what else makes Azure Synapse a good choice for businesses? Here are a few features we like:

Illustration with globe and Azure Synapse logo

1. Improved cost control quotas

A common concern with serverless offerings is that there is no way to control costs. Since organizations usually pay by data processed per query, it’s quite possible to quickly go over budget by simply running a very heavy query.

Azure Synapse now allows you to set daily, weekly and monthly limits to help keep organizations within their budget.

2. Better integration with Azure Auto ML services

The integration between Synapse and Azure Auto ML services now allows you to follow a simple visual wizard to score a table against an existing model.

This feature has been a part of the SQL server for a while, but it all had to be done by code. Following a simple visual wizard will save you a lot of time, especially when evaluating a model.

3. New T-SQL features

The new update expands the set of allowed T-SQL constructs by adding support for STRING_AGG, OFFSET/FETCH, CONTEXT_INFO, SESSION_CONTEXT, and pivot/unpivot

The context functions allow for easy maintenance since it eradicates the need to depend on some sort of state external table on storage. This feature is still growing, and we expect further updates in subsequent months

4. Enhanced role-based access controls

During initial iterations of Azure Synapse, the RBAC roles allowed far too much functionality on each role. This became a problem since Synapse was designed as a collaborative environment.

The new and improved RBAC controls now add multiple new roles to control more specific features and promotes proper segregation of roles

Getting started with Azure Synapse

If your organization is considering migrating to Azure Synapse, Neal Analytics can help. Being a Microsoft Gold Partner since 2011, Neal holds deep expertise in running end-to-end migration projects and can jump in to help out at any stage of the migration process.

Neal can now help organizations plan and budget their SQL Server migration to Azure via Microsoft’s Azure Migration Engagement (AME) program. Click here to learn more. 

If you are ready to take the next step towards migrating to Azure Synapse Analytics, contact us.

This blog was originally published 8/10/2021 and has since been updated.