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Category: Synapse Analytics

Combining Azure Synapse Analytics and Azure Purview

Wolfgang Strasser shows how we can integrate Azure Synapse Analytics with Azure Purview:

In the past months I had the chance to play with and build solutions based on Azure Synapse Analytics and Azure Purview.

Azure Synapse (my Synapse blog entries) as the foundation for a solid platform to store, analyze and build data solutions and Azure Purview (my Purview blog posts) as the data governance and data catalog solution in Azure.

During the writing of my latest blog post (What’s new in Azure Synapse Analytics?), I found a very interesting entry in the update feature list: Azure Purview Integration.

Read on to see how.

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Optimizing a SQL Server 2019 Project for a Dedicated SQL Pool

Kevin Chant shows us how we can modify a database schema intended for SQL Server 2019 to work best with an Azure Synapse Analytics dedicated SQL pool:

In this post I want to cover how you can transform your SQL Server database schema for a dedicated SQL Pool if you are using Azure DevOps. Because I covered it at Data Toboggan over the weekend and it can be very useful.

By the end of this post, you will know one way you can transform the schema of a database project for SQL Server 2019 if you are using Azure DevOps. So that you can make it optimal for dedicated SQL Pools.

Click through for the process and an example. Note that this isn’t a quick “check this box and you’re done” type of solution, but if you already have a proper star schema, this will help you think through some of the things you’ll need to do.

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Using Spark Pools in Azure Synapse Analytics

Rahul Mehta shows how to create and use an Apache Spark pool in Azure Synapse Analytics:

In the last part of the Azure Synapse Analytics article series, we learned how to create a dedicated SQL pool. Azure Synapse support three different types of pools – on-demand SQL pool, dedicated SQL pool and Spark pool. Spark provides an in-memory distributed processing framework for big data analytics, which suits many big data analytics use-cases. Azure Synapse Analytics provides mechanisms to use SQL on-demand pool to query data as a service, SQL dedicated pool for data warehousing using distributed data processing engine, and Spark pool for analytics using in-memory big data processing engine. This article shows how to create a Spark pool in Azure Synapse Analytics and further how to process the data using it.

Click through for a demo on setup and a sample notebook to get started.

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Auto-Pausing Dedicated SQL Pools in Azure Synapse Analytics

Fonseca Sergio automates an important cost-saving measure when working with Azure Synapse Analytics dedicated SQL pools:

As Synapse engineer or Synapse Support Engineer you may need to start and test some Pools, and you want this to be the most cost efficient possible. Leaving some Synapse with a lot of DWU left turned on during the weekend because you forget to pause the DW after you shutdown your computers is not a good approach and we can quickly resolve this by using Powershell + Automation accounts.

This is also a good introduction to Azure Automation if you aren’t familiar with it.

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External Table Not Accessible because Content of Directory Cannot be Listed

Liliam Leme troubleshoots an error when working with a serverless SQL pool in Azure Synapse Analytics:

Following this lab: Lab: Serverless Synapse – From Spark to SQL On Demand – Microsoft Tech Community

You may experience this message: 

Failed to execute the query because content of directory cannot be listed) 

This is due to an extra step required to enable the AAD to pass through the firewall on the storage.

Click through for the solution.

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Integrating Power BI with Azure Synapse Analytics

Santosh Balasubramanian walks us through the process of querying Azure Synapse Analytics data with Power BI:

In this guide, you will be integrating an already-existing Power BI workspace with Azure Synapse Analytics so that you can quickly access datasets, edit reports directly in the Synapse Studio, and automatically see updates to the report in the Power BI workspace. We will be using a Power BI report developed using the Movie Analytics dataset of the previous guide to show the functionalities of the Power BI integration in Azure Synapse.

Click through for the demo.

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Working with Serverless and Dedicated SQL Pools in Azure Synapse Analytics

Igor Stanko takes us through both dedicated and serverless SQL Pools in Azure Synapse Analytics:

Both serverless and dedicated SQL pools can be used within the same Synapse workspace, providing the flexibility to choose one or both options to cost-effectively manage your SQL analytics workloads. With Azure Synapse, you can use T-SQL to directly query data within a data lake for rapid data exploration and take advantage of the full capabilities of a data warehouse for more predictable and mission-critical workloads. With both query options available, you can choose the most cost-effective option for each of your use cases, resulting in cost savings across your business.

This post explores 2 consumption choices when exercising analytics using Synapse SQL (serverless and dedicated SQL pools) and examines the power and flexibility provided by Azure Synapse when both are used to execute T-SQL workloads. In addition, we will explore options to control cost when using both models.

Click through for details, including hints on minimizing costs.

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