Azure

Moving Azure SQL Database from One Subscription to Another

Multiple Environments

Many companies like to separate Production from Development / UAT environments. I have frequently seen Dev / UAT deployed to one subscription, and Production to a different subscription. This works well for the Finance team because the billing for each environment is separated. However, having the environments in different subscriptions inserts a speed bump in a common practice among DBAs – restoring a copy of the Production database in the UAT and Dev environments to ensure that code is synchronized across all environments.

Azure SQL Database Restore Database 

In Azure SQL Database, when you select “Restore”, your options are limited to restoring the same server. Notice that the options for changing the subscription, resource group, and server are greyed out. Only the database name can be changed.

If you need to restore a copy of your Azure SQL database on the same server so that you can copy a deleted table back into your database, then this works fine.

The restore Azure SQL database operation will not allow restoring the database over the existing database, however, you can change the name of the database at any time.

 

Rename Azure SQL Database

In SQL Server Management Studio run the following command on your Azure SQL Server:

ALTER DATABASE OriginalDatabaseName MODIFY NAME = NewDatabaseName;

 

Azure SQL Database Copy Database

The next option would be to COPY the database. This option looks promising because it allows the database to be copied to another server, and if a different Azure SQL server does not exist, a new one may be created without having to leave the Copy dialog and create one separately.

Although the New Server option looks promising, it does not provide the desired options: changing the subscription and resource group.

All is not lost, a solution exists: since an Azure SQL Server can move from one Subscription to another, the database can be copied to a Migration server, moved to the other Subscription then copied onto the existing server to refresh the existing database.

It’s Easier than It Sounds

You must have at least Contributor rights in both subscriptions to successfully perform this operation.

  • Copy the Azure SQL Database to a new migration Azure SQL server using the “Copy database” blade as shown above. This server will exist only for the duration of the database transfer and can be deleted immediately following the completion of the process
  • Go to the Migration Azure SQL Server’s Overview page

  • Click on “Move” and select “Move to another subscription” in the drop list

In the above example, the user does not have access to move resources to the selected resource group.

  • With appropriate permissions, the next step is the validation of resources to move

(The above image is linked to the image in Microsoft Documents “Move resources to a new subscription” article because my account doesn’t have rights to perform this action so I cannot get a good screenshot. The validation dialog should show only the Migration Azure SQL server in this step.)

  • Upon completion of Validation, the Review screen pops up

  • Confirm Source and Target subscriptions, resource groups, and several resources to move then check the box and click “Move”
  • Azure will pop up a notification when the move has been completed
  • Go to the subscription and resource group where the Migration server has moved
  • Go to the overview page of your Azure SQL Database on the Migration server
  • Click on “Copy”
  • Select your UAT or Dev Azure SQL Server and set the database name
  • Click on “Review + Create”
  • Click on “Create” to complete the process

Upon successful completion of the deployment, the migration server may be deleted.

If you have questions about Azure SQL Database, either how to use it or how to implement it in your organization, reach out to us. Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or  [email protected].

Andie LetourneauMoving Azure SQL Database from One Subscription to Another
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MLOps: How To Automate The Machine Learning Model Pipeline

Machine learning, an application of artificial intelligence (AI) that allows computers to automatically learn and improve based on experience, is often regarded as one of the most advanced industries on the planet. The time it takes to move from concept to manufacture and generate economic value is a significant barrier in the industry.

 

In a recent webinar, hosted by Data Analytics Consultant Brad Jarrett, we offered an overview of machine learning and the Azure Machine Learning Service. We also looked at essential principles in the machine learning (ML) CI/CD process.

 

Additional topics covered:

  • How to efficiently get a model deployed into production
  • What tools are available on the market
  • The ML model lifecycle

 

If you are concerned about testing and approval gates or worried about model performance and data drifting, this webinar is for you. You can watch the entire webinar by clicking the link below.

 

Be sure to join us each week for our free webinars that happen every Tuesday at 11 AM ET. Our webinars cover a wide range of Azure topics and are presented by industry experts. Check out what webinars are coming up on our events calendar.

Need further help? Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or  [email protected].

3CloudMLOps: How To Automate The Machine Learning Model Pipeline
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Azure Databricks in the Modern Data Warehouse

The Modern Data Warehouse is an architecture that considers the way we consume, analyze, and distribute data. Today, businesses use Azure Synapse Analytics to build brand-new data warehouses in the cloud. When your data transfer to the cloud is supported by an effective data management platform, you can quickly deliver accessible, timely, and actionable data to drive innovative business decisions.

In a recent webinar, hosted by Principle Data Architect, Rowland Gosling we discussed how to utilize Azure Databricks to transport data from a variety of data sources into Azure Data Lake, Synapse Analytics, and visualize using Power BI’s streaming capabilities.

Additional topics covered:

  • The evolution of Data Warehouse
  • What is Azure Databricks
  • The importance of Azure Databricks

If you are looking to modernize your data warehouse or use Azure Databricks to transport data from various sources, this webinar is for you. You can view the complete webinar by clicking on the link provided below.

Be sure to join us each week for our free webinars that happen every Tuesday at 11 AM ET. Our webinars cover a wide range of Azure topics and are presented by industry experts. Check out what webinars are coming up on our events calendar.

Need further help? Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or  [email protected].

3CloudAzure Databricks in the Modern Data Warehouse
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Azure SQL Edge

What do you know about Azure SQL Edge? This relational database engine has all the goodness we’re used to in SQL Server but is geared for IoT and IoT Edge deployments. It gives you the capabilities to create a high-performance data storage and processing layer for IoT applications and apps.
Data is constantly being captured by IoT devices. Many industries, including oil and gas, mining, and even farming, are adopting massive, complex machines with tons of sensors that collect data. That data is collected, sorted through, and used in a variety of ways to assist them in their operations. This is all IoT in action.

However, there are issues: asynchronous communications are required due to intermittent network access, gaps in time, missing values with IoT time series data, data retention, and management (small devices = little storage).
In this video, I dive into more about Azure SQL Edge and how it can help with common challenges. Topics I cover are:
• Typical Azure SQL Edge Workloads – Data, Machine Learning, and Analytics
• Data Lifecycle in the Edge
• Benefits of SQL Edge including near real-time response and reduced IoT costs
• I’ll also discuss how Azure SQL Edge is NOT SQL Server – I point out the things you won’t get but you’re used to in SQL Server, as well as tell you what you do get from SQL Edge for your IoT data.
The last part of my video is spent on a demo of Azure SQL Edge, so be sure to check that out.

In summary, Azure SQL Edge is built for IoT workloads directly on the device and it runs on Linux. There are many good resources out there to help you get started, and although it’s not the same as SQL Server, it is very comfortable and familiar to those of us who have been on SQL Server. I suggest you give it a try for your IoT solutions and apps.

Need further help? Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or [email protected]

Jon BloomAzure SQL Edge
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Azure Data Modern Platform

Are you using your data as an asset to make predictions about your business? Some challenges that many businesses face are, large volumes of incoming data which they are unable to process and derive insights from, and data silos that make it difficult to find and share data as it’s spread across multiple sources within the organization, as well as slow adoption of AI/ML and real-time analytics. A Modern Data Platform in Azure can help overcome these challenges.

First, let’s look at how we got here from the Microsoft business intelligence we’ve had for over 20 years. In the past, most products were on premises, using SQL Server for our storage and ELT, master data, and data quality, and static reporting with SQL Server Reporting Services (SSRS). Security was in multiple places and change management was manual with much room for errors. Our data dictionary consisted of tables and field types, typically in Excel, and got outdated quickly and was hard to find as it was buried somewhere on the network.

Now in the cloud, the transition is surely for the better.
• Storage – we have a variety of options including Azure SQL Database, Azure Synapse, blob storage and Cosmos DB.
• ETL – we now use Azure Data Factory or Databricks.
• Delivery – reports are in Power BI in the form of dashboards and SSRS reports are being converted to paginated reports.
• Master Data and Data Quality – we have a variety of 3rd party vendors we are partnered with.
• Security – we can leverage Azure Key Vault, Azure RBAC which consists of roles assigned to people and groups, and service principles for some of our automation.
• Change Management – Azure DevOps boards enable us to set up tasks in sprints of time to bite off a chunk of work to complete, then update the ticket when complete, test, and move to production.
• Source Code Repository – Azure DevOps Git.
• Data Dictionary, Data Lineage, and Data Sensitivity – we have the new Azure Purview and this fills in a lot of gaps we had in the past.

If we look at the analytical maturity curve. (Please see the chart outlining this in my video.) We began with basic, static reports with limited Ad hoc and a single version of the truth and mainly created by IT. Now we’ve moved to self-service reporting with large ad hoc and we’re not dependent on IT for report creation. With Power BI we have empowered the user to build their own reports to investigate the data and gain insights to run the business, increase sales, streamline processes, and lower costs.
Predictive analytics is where we form models and allow machine learning to process the data and look for patterns over time. We can then move through the analytical maturity curve to real-time analytics and finally, real-time predictive modeling and mining which is event-based and allows for data discovery.

As you can see, we’ve come a long way over the years and a Modern Data Platform in Azure gives you a solid platform in which to run your business in the cloud and to better manage your data. Throw in data governance and Azure can handle most, if not all, of your data needs.

 

If you want to learn more about an Azure Modern Data Platform for your business, our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or [email protected].

Jon BloomAzure Data Modern Platform
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Azure Data Factory – Let’s Make Some Data

Is it true to say that Azure Data Factory generates data? Of course not, but it allows you to improve, strengthen, and speed up your data without spending $6 million. How is this even possible? Azure Data Factory is a tool that allows you to collect, store, transform, integrate, and prepare data in a single location. The ability to automate and schedule tasks allows users to save not only time but also money.

In a recent webinar led by Lead Data Architect, Leslie Andrews, we discussed the fundamentals of Azure Data Factory, including what it DOES, the components used in the Factory, and how to create a basic Factory output. We also learned the basics of being a Data Factory machinist and how to rebuild your data!

Additional topics covered:

  • Creating a Data Factory Pipeline
  • Setting up Azure Data Factory
  • A real-world example of how to use Azure Data Factory.

If you want to learn the fundamentals of Azure technology or brush up on how to perform basic tasks within Data Factory, this webinar is for you. You can view the entire webinar by clicking the link below.

 

Be sure to join us each week for our free webinars that happen every Tuesday at 11 AM ET. Our webinars cover a wide range of Azure topics and are presented by industry experts. Check out what webinars are coming up on our events calendar.

Need further help? Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or  [email protected].

3CloudAzure Data Factory – Let’s Make Some Data
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Using Azure ML and Cognitive Services to Improve Business Outcomes

Businesses today have an immediate need to store large amounts of data in formats such as Word, Excel, PDF, images, videos, text files, and other sources for long periods. Azure ML and Azure Cognitive Services are critical tools in assisting businesses in leveraging their data and enhancing business outcomes.

In this recent webinar presented by Principal Data Architect, Rowland Gosling, we explored how to leverage your existing data and how AI can be useful to businesses. The presenter also looks at Knowledge Mining with Azure Search and the Machine Learning lifecycle.

Additional topics covered:

  • Azure Search to translate from multiple languages into English
  • How to train a Machine Learning model to recognize good/bad items
  • The capabilities of Machine Learning built into Power BI

If you are concerned about technology disruption or wanting to better leverage your data using Azure ML and Cognitive Services, then this webinar is right for you. You can watch the complete webinar below.

Be sure to join us each week for our free webinars that happen every Tuesday at 11 AM ET. Our webinars cover a wide range of Azure topics and are presented by industry experts. Check out what webinars are coming up on our events calendar.

Need further help? Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or  [email protected].

3CloudUsing Azure ML and Cognitive Services to Improve Business Outcomes
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Simplify Dataverse Data Imports Using Data Flows

Have you ever wished there was a more efficient way to import data into your Dataverse (Common Data Service) database? In most cases, creating an app generally requires data from more than one source. While this can often be achieved at the application level, there are occasions when combining this data into a common store makes app development simpler and allows for a consistent set of logic to manage and run across all applications.

In a recent webinar by Senior Consultant, Sharon Woloshin, we examined how to use Data Flows to transform and clean your data before SIMPLE import into your Dataverse database. Sharon also explored how to replace Excel data imports and how to prepare your data for import using Azure dataflows and Power Query Online.

Additional topics covered:

  • How to use Dataverse as a home for data maintained in less convenient locations.
  • How to use dataflows to clean and transform your data before importing it into Dataverse.
  • How to simplify dataflow connections to replace complex and trouble-prone Excel imports into Dataverse.

If you are interested in strategies on how to use dataflows to transform and clean your data before a SIMPLE import, then this webinar is right for you. You can watch the complete webinar below.

Be sure to join us each week for our free webinars that happen every Tuesday at 11 AM ET. Our webinars cover a wide range of Azure topics and are presented by industry experts. Check out what webinars are coming up on our events calendar.

Need further help? Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or  [email protected].

3CloudSimplify Dataverse Data Imports Using Data Flows
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Introduction to Azure Synapse Analytics

Are you interested in learning how to combine your data with the ability to query data on your terms? Azure Synapse Analytics is a boundless analytics service that combines data integration, enterprise data warehousing, and big data analytics into a single platform. This tool enables users to bring their worlds together by providing a combined experience for ingesting, exploring, preparing, managing, and serving data.

In a recent webinar by Lead Data Architect, Brian Custer, we examined the Azure Synapse Analytics unified analytics workspace and discussed the major use cases and scenarios for using the platform. Brian also spends time on examining the Azure interface.

Additional topics covered:

  • How to set up a workspace in Azure
  • How to work with the major features of the studio
  • Analyzing NYC taxicab data

If you’re looking for a unified analytics workspace to engineer and analyze big data, Azure Synapse is the answer, and this webinar will give you a great introduction to Synapse. You can watch the entire webinar by clicking the link below.

Be sure to join us each week for our free webinars that happen every Tuesday at 11 AM ET. Our webinars cover a wide range of Azure topics and are presented by industry experts. Check out what webinars are coming up on our events calendar.

Need further help? Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or  [email protected].

3CloudIntroduction to Azure Synapse Analytics
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Serverless Pools in Synapse Analytics Workspace

Hopefully, you’ve already heard about Azure Synapse. One of the newest Azure offerings, Synapse is a limitless analytics service that brings together, data warehousing, enterprise data warehousing, and big data analytics. I’d like to tell you about the “launchpad” for all things Synapse – Synapse workspaces.

With Synapse workspaces you can do many things including development, ETL, ELT, DevOps, Azure ML, and Power BI. When you create a new workspace, you automatically get a serverless pool.

  • When you go into your workspace, you’ll see Activity Hubs in Synapse Studio. These hubs organize the tasks needed for building analytics solutions.
  • Synapse Studio is divided into Activity hubs; there are currently 6 hubs:
    • Overview and data – where we can explore all our structured/unstructured data
    • Develop – the development hub where you can use workbooks, SQL, etc.
    • Orchestrate, monitor, and manage – these look like Azure Data Factory, they have the same look & feel and do the same jobs.
  • Pools are comparable to databases in Synapse Analytics. There are 3 kinds of pools; serverless, dedicated, and Spark.
  • Each workspace has a serverless pool by default.
    • In my serverless pool cheat sheet (To see this, please watch my video included), you’ll see we have Spark, Cosmos DB, and Azure Data Lake store as the 3 data sources you can use.
    • The input types are Parquet, CSV, and JSON. Parquet is the better way to do things as it’s compressed, so it only has to read a large piece of the data in a compressed format into memory. In other words, it doesn’t have to go back to the well as often.
    • Also, think about portioning your data in some logical way when you begin working with this. This way, if your data doesn’t belong to a certain partition, it won’t go looking for it somewhere it’s not.
    • Also, think about different landing zones for different data (refer to the flow chart on my cheat sheet).

In my video, I demo how to use a Synapse Analytics workspace so be sure to check that out. I’ll walk you through how a workspace, as well as how serverless, works.

My advice is to go in the Azure portal and give Azure Synapse Analytics workspace a try. Play around with it and see what you can do.

Quickstart in Microsoft docs: https://docs.microsoft.com/en-us/azure/synapse-analytics/quickstart-create-workspace

 


If you have questions about Azure Synapse Analytics, either how to use it or how to implement it in your organization, reach out to us. Our expert team and solution offerings can help your business with any Azure product or service, including Managed Services offerings. Contact us at 888-8AZURE or  [email protected].

Rowland GoslingServerless Pools in Synapse Analytics Workspace
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