A Fine Slice Of SQL Server
So in the last blog we confirmed that we could move to SQL MI via some analysis, this is now time to actually do a backup and restore via URLs to move data.
Quite simply you need to BACKUP to URL (Azure Storage container) and the setup requirement is that you need to create a SQL credential that holds the SAS token – this is what allows authentication to the container to take place.
Click through for the process.
Leave a CommentDennes Torres notes a new button on the ARM Template deployment screen:
Recently a new feature appeared in Azure Portal, an ARM Template Visualizer, capable to show a graphic view of the resources inside an ARM template. The feature appears as a new button in screens where we are editing or downloading templates.
Click through to see it in action.
Leave a CommentArun Sirpal wants to restore a database:
Now that we have a Managed Instance built, the next question is how do we get data across? I will break this up into separate posts but the lesson for this blog post is ANALYSIS FIRST!
Click through for the analysis.
Leave a CommentAveek Das explains the notion of Azure Time Series Insights:
In this article, we are going to learn in detail about Azure Time Series Insights. Microsoft Azure is one of the leading cloud providers these days. With a lot of companies adopting or migrating to the cloud these days, it has become a usual trend to convert existing technologies into cloud-based services and consume them. This not only helps the companies to reduce their cost but also in turn allows them to focus on more business-related problems rather than concentrating on infrastructure costs.
Azure Time Series Insights is one of the cloud services that users can use to integrate with their data that is constantly changing with time such as data from various sensors or machines, data from satellites, airlines etc. Any data that can be generated on a high scale and needs to be analysed, can be used through Azure Time Series Insights. In this article, we will focus on a high-level introduction of this service along with some use cases in detail.
Read on for the article.
Leave a CommentMatthew Rhodes, et al, take us through an interesting case study:
According to a recent study, defective products cost industries over $2 billion from 2012–2017. Defect detection within manufacturing is an important business use case, especially in high-value product industries like the automotive industry. This allows for early diagnosis of anomalies to improve production line efficacy and product quality, and saves capital costs. Although advanced anomaly detection systems employ sensors as well as Internet of Things (IoT) devices to collect multimodal data to improve performance, computer vision continues to be a common approach. Detecting anomalies in automotive parts and components using computer vision can be done using normal images, and even X-Ray based images for structural damages. Recent advances in deep learning and computer vision have allowed scientists and manufacturers to develop enhanced anomaly detection systems, including surface defect detection on automotive body panels and dent detection in vehicles.
Read on for case notes.
Leave a CommentKendra Little is fairly pleased with the Azure SQL Database Quickstart guide:
I’m working through a series of Quickstart tutorials for Azure SQL Database and sharing bite-sized reviews.
In this first walkthrough, I’m stepping through the Create a Single Database tutorial.
Click through for Kendra’s take.
Leave a CommentDave Ruijter shows how you can use Azure DevOps to perform automatic semantic versioning:
I am a fan of using semantic versioning (a.k.a. SemVer) for data solutions, following the v1.0.0 pattern. It helps in the communication between team members and stakeholders, by limiting ambiguity and misunderstandings related to the version of your solution’s releases. With semantic versioning, the trick is to increment the version according to the changes you have made since the latest release. Manually keeping track of that is not an easy task, especially for small teams, without the capacity to have somebody dedicated to this administration task. I found a way to make this a lot easier, leaning on the Pull Request description! And as a bonus, we will create some nice release notes automatically
Click through to see what you need to have set up on your Azure DevOps subscription and a detailed walkthrough of how to set it up.
Leave a CommentMarc Lelijveld wants to swap a connection from using Azure Analysis Services to Power BI Premium:
Having the context of an Azure Analysis Services dataset that is migrated to Power BI Premium, you might have to rebind many reports. Especially if this dataset is positioned as being a managed dataset that is also used for self-service purposes and has many related reports.
In this blog I will elaborate on how you can easily rebind all these reports to the new Power BI dataset, without downloading all reports and manual rebinding.
It’s not a trivial operation, but it is a lot easier than updating each entry individually.
Leave a CommentHope Foley shows how you can set up Powershell to be your Azure Cloud Shell language of choice:
Part of my job is doing POCs with customers to help with Azure Data Services. Anything that helps me move quicker is helpful so I’m a tad bit obsessed with automating things. I have used PowerShell for more years than I’m willing to admit to help me automate what I can. There are a lot of ways to automate things like ARM templates and DevOps, but PoSH has been my preferred hammer. As much as I love it, I’ve ran into issue sometimes with installing modules locally on folks machines and not to mention if they have a Mac. I wondered recently if Azure Cloud Shell would help make things easier, and it very much did and I’m super pumped to share! This post will help run through how to get setup to run PowerShell scripts in Azure.
For people who prefer Powershell to bash, check it out.
Leave a CommentAveek Das shows how you can use Azure Queue Storage as a way to trigger an Azure Function App:
In this article, we are going to learn how to trigger Function Apps from Queue Storage in Azure. Function Apps has been one of the most popular cloud services of Microsoft Azure. Function Apps allow users to write code in any language and then execute the code in the cloud. There is no infrastructure to be managed and hence is very flexible for writing and building applications on the go. Every Function App can be triggered in multiple ways, for example, by calling the function URL using an HTTP endpoint or from some other functions in Azure. In this article, we are going to trigger the Function App from Queue Storage in Azure and see how to pass a message from the queue to the Function App.
Queue Storage in Azure is another service in Azure that allows users to store multiple messages in it. Users can use a queue to create a list of items that need to be processed one by one. Messages to Queue Storage in Azure can be added by using the HTTP or HTTPS endpoints. Usually, a queue can store data up to 64 KB in size. We can add millions of messages in a queue if it is supported by the storage account.
Click through to see how. Though now I wonder why I might use Queue Storage instead of an Event Hub or an Event Grid. But I suppose that’s a question for a different article.
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