The Linked Service for ML is going to need some information from the Web Service, the URL and the API key. Chances are neither of these have been committed to memory, instead open up Azure ML, go to Web Service and copy them. For the URL, look under the API Help Pagegrid, there are two options, Request/Response and Batch Execution. Clicking on Batch Execution loads a new page Batch Execution API Document. The URL can be found under Request URI. When copying the URL, you do not need to include any text after the word “jobs”. The rest of the URL, “?api-version=2.0”. Copying the entire URL will cause an error. Going back to the web Services page, The API Key appears on the dashboard section of Azure ML and there is a convenient button for copying it. Using these two pieces of information, it is now possible to create the Data Factory Linked Service to make the connection to the web service, which here I called AzureMLLinkedService
Read the whole thing.
Over the last year, I have been intentionally seeking out to get feedback from the community via various SQL events, particularly those who plan to use or are currently using Azure SQL Database. A lot of questions have come up about managing Azure SQL Database better – i.e. being more proactive and more responsive in managing Azure SQL Database. One of the ways to be more proactive about your SQL Database is by setting up alerts. As an example, you can create an alert in case DTU goes above 95% – say in the last 5 minutes, so that you can either investigate why this might be or upgrade it to a higher SKU.
This article walks through how you can setup an Alert on Azure SQL DB.
I really like the fact that they offer web hooks; that way, I can integrate these alerts with Slack or other messaging systems.
T-SQL Differences in Azure SQL Database
I used to think this was the real difference between SQL Server and SQL Database. I was wrong. Really wrong. But it’s a good place to start. Now from what I can tell everything in Azure is a moving target. There are constant changes so it’s important to know where the documentation is. In this particular case here it is: Azure SQL Database Transact-SQL differences.
Check it out. The differences are smaller than in the past, but I expect that there will always be some differences—particularly on the administration side—due to the nature of Azure SQL Database as a PaaS offering.
Once the cluster is created, you can connect to the edge node where MRS is already pre-installed by SSHing to r-server.YOURCLUSTERNAME-ssh.azurehdinsight.net with the credentials which you supplied during the cluster creation process. In order to do this in MobaXterm, you can go to Sessions, then New Sessions and then SSH.
The default installation of HDI Spark on Linux cluster does not come with RStudio Server installed on the edge node. RStudio Server is a popular open source integrated development environment (IDE) available for R that provides a browser-based IDE for use by remote clients. This tool allows you to benefit from all the power of R, Spark and Microsoft HDInsight cluster through your browser. In order to install RStudio you can follow the steps detailed in the guide, which reduces to running a script on the edge node.
If you’ve been meaning to get further into Spark & R, this is a great article to follow along with on your own.
“Thanks to SQL Threat Detection, we were able to detect and fix code vulnerabilities to SQL injection attacks and prevent potential threats to our database. I was extremely impressed how simple it was to enable threat detection policy using the Azure portal, which required no modifications to our SQL client applications. A while after enabling SQL Threat Detection, we received an email notification about ‘An application error that may indicate a vulnerability to SQL injection attacks’. The notification provided details of the suspicious activity and recommended concrete actions to further investigate and remediate the threat. The alert helped me to track down the source my error and pointed me to the Microsoft documentation that thoroughly explained how to fix my code. As the head of IT for an information technology and services company, I now guide my team to turn on SQL Auditing and Threat Detection on all our projects, because it gives us another layer of protection and is like having a free security expert on our team.”
Anything which helps kill SQL injection for good makes me happy.
Since you are right at the start of your career, you may as well plan on maximizing the life of the knowledge and skills you’re building. By this, I mean spend your time learning the newest and most advanced software rather than the old approach. Is there still work for people who only know SQL Server 2000? Sure. However, if you’re looking at the future, I strongly advocate for going with online, cloud-based systems. This is because, more and more, you’re going to be working with online, connected, applications. If the app is in the cloud, so should the data be. Azure and the technologies within it are absolutely the cutting edge today. Spending your limited learning time on this technology is an investment in your future.
This answer is a tougher call for me. Looking at new database developers (or development DBAs or database engineers or whatever…), I think the case is pretty solid: there’s so much skill overlap that it’s relatively easy to move from Azure SQL Database to on-prem. With production DBAs, the story’s a little different: as Grant mentions, this is a Platform as a Service technology, and so the management interface is going to be different. There are quite a few commonalities (common DMVs, some common functionality), but Grant gives a good example of something which is quite different between the PaaS offering and the on-prem offering: database backup and restoration. I think the amount of skills transfer is lower, and so the question becomes whether the marginal value of learning PaaS before IaaS/on-prem is high enough. Given my (likely biased) discussions of Azure SQL Database implementations at companies, I’d stick with learning on-prem first because you’re much more likely to find a company with an on-prem SQL Server installation than an Azure SQL Database.
Power BI Embedded is the reporting and analysis solution for mobile and web applications. Power BI Embedded is an Azure service that integrates Power BI solution into mobile and web applications. The report still has to be authored and created in Power BI Desktop. After creating the report it can be published into Power BI workspace in Azure, and using API Keys of Power BI workspace and embedding Power BI report frame into the web/mobile application it will be integrated into the application.
Reza walks through the process step-by-step. The upshot is that you can take this report you created in Power BI and embed it into your own application, where you can apply your own in-app access controls. There are limitations, which Reza spells out at the end of the post, so check it out.
With that String parameters, it is easy to just type what I want in the textbox. But, for the PSCredential parameter at the bottom, I was unsure what to do. I figured, since this is just a textbox, I couldn’t just magically pass in a Credential Asset. So, I tried passing in an expression that used the Get-AzureRmAutomationCredential cmdlet that returns the Credential Asset specified. That didn’t work very well. I then started digging through documentation, figuring I would see references and examples of passing a Credential Asset in the Test Pane. It took me a bit, but I finally landed on an Azure.com blog post titled Azure Automation: Runbook Input, Output, and Nested Runbooks. While this post didn’t match all that closely with the search criteria around the Test Pane, it did contain my answer in a section on starting Runbooks:
The answer turns out to be pretty simple.
Most data warehouses and data marts require a date dimension or calendar table. Those of us that have been building data warehouses in SQL Server for a while have collected our favorite scripts to build out a date dimension. For a standard date dimension, I am a fan of Aaron Bertrand’s script posted on MSSQLTips.com. But the current version (as of Aug 8, 2016) of Azure SQL Data Warehouse doesn’t support computed columns, which are used in Aaron’s script.
Click through for the script.