Modern applications don’t function in isolation. To get the most out of the enterprise apps you build or buy, you’ll have to connect it to other applications. In other words, data engineers have to engage in effective application integration to achieve their business goals.

Sometimes, this means connecting one application directly to another. But this is a rare occurrence in digitally transformed industries. More often than not, application integration means successfully connecting multiple independent systems.

This is one of the reasons why enterprises across industries moved from on-premise data centers onto the cloud. Today, tech giants like Amazon, Google, and Microsoft all offer cloud computing solutions that are specifically built to engage in data and analytics. But for this post, we’re going to focus on Microsoft Azure.

Why Microsoft Azure?

Microsoft Azure can be described as a continuously expanding and evolving cloud services solution that helps companies meet their business challenges effectively. You can build any type of app and deploy it utilizing your team's existing skill sets and tools and deploy it anywhere.

Building smart apps is also quite easy on Azure. This is because you can use any tools, frameworks, and programming languages. Valuable insights can be derived by leveraging native artificial intelligence and analytics solutions.

The rich set of cognitive APIs on offer can also deploy human-like intelligence into your custom apps. Some of these include Computer Vision, Custom Vision, Face (recognition), Form Recognizer, Ink Recognizer, and Video Indexer. No matter where your data lives, you can leverage Azure to unlock its potential and make intelligent business decisions.

What Are the Available Data Tools?

When you sign up for Azure, your organization will be able to take advantage of a fully managed, elastic data warehouse. In this scenario, you’ll get security at every level of scale at no extra cost.

Microsoft Azure Databases

Data and Analytics Tools

Related Tools

  • Cognitive Services (to enable contextual interaction by adding smart API capabilities)
  • Azure Bot Service (a smart serverless bot service that can be scaled up or down on demand)
  • Azure Developer Tools (to build, deploy, diagnose, and manage multi-platform scalable apps and services)

This fully managed cloud service solution also has the option of managed on-demand pay-per-job analytics service and real-time stream processing service. This offering is backed by enterprise-grade security, auditing, and support.

You can also build massive data lakes because there aren’t any limits. This means that you can engage in large-scale parallel analytics projects. This can be achieved by utilizing the quick, simple, and collaborative Apache Spark-based analytics platform.

Microsoft also provides a data integration service to orchestrate and automate data movement and transformation. This, however, can become highly complicated very quickly.  

That’s why more and more companies are now using integration-Platform-as-a-Service (iPaaS) solutions like Xplenty.    

What’s Xplenty?

Xplenty is a cloud-integration solution that helps businesses integrate, process, and prepare data for analytics in the cloud. This means that you can use our pack designer to deploy a wide variety of data integration use cases like data preparation, replication, and transformation.

All this can be achieved seamlessly within a point-and-click environment. This turnkey data transformation solution enables users to execute packages from the API or user interface. So you can easily integrate data from more than 100 different Software-as-a-Service applications and data stores.

When you engage in data and analytics with a highly integrated solution, you can deliver highly personalized experiences, hold on to critical data indefinitely, boost efficiency, and save money.

At first glance, Microsoft Azure and Xplenty might seem like highly incompatible competing platforms, but this is not exactly true. In reality, both platforms and their related data tools can be used together to derive real business value. Xplenty's rich set of connectors enables data to securely flow into your Azure infrastructure from all your business systems.

But how should you go about this? Let’s take a look.

Enable Xplenty Access to Azure SQL Databases

While it can sound quite complicated, it’s quite easy to get Xplenty to read data from your Microsoft Azure SQL databases. It’s also pretty straight forward when it comes to writing data to them.

To enable access to your Azure SQL databases, you have to follow the eight steps listed below:

  1. First, add rules to the database firewall. This will allow access for Xplenty's IP addresses. Next, add a rule for each IP address that is relevant to your account’s region using the following LIST.
  2. Add a SQL Server connection to your account.
  3. Enter your Azure SQL database hostname and the server name.
  4. Choose the pattern user@server_name as your user name. Then replace the user with the user designated for Xplenty and server_name with your Azure SQL database server name.
  5. Enter the user's password.
  6. Enter the database name.
  7. Click Test Connection to ensure that the connection details are correct.
  8. Click Create Microsoft SQL Server Connection to create this new connection.


Enable Xplenty Access to Data on Azure Blob Storage

Microsoft Azure Blob storage can be described as a data tool that stores unstructured data in the cloud as blobs or objects. This means that you can store just about any type of binary data or text, including application installers, documents, media files, and more.

To allow access to data living in Azure Blob Storage, you have to first make a connection. To get the ball rolling, you have to first get your Azure storage account details to use in Xplenty.

How do you do this?

  1. Navigate to the Azure Portal and select Storage Accounts from the portal menu.
  2. Then choose the storage account you would like Xplenty to access.
  3. Click All Settings.
  4. Click Access Keys.
  5. Then follow the steps to create a new connection in Xplenty using the information from your storage account access keys screen.


To connect Azure Blob Storage to Xplenty, you have to do the following:

  1. Click on your avatar at the top right of the screen and select Manage Connections.
  2. To set up a new connection, click New Connection.
  3. Next, select Azure Blob Storage.
  4. At this juncture, you will be asked to fill in the Account Name of your Azure storage account.
  5. Enter the Access Key with one of the access keys for your Azure storage account.
  6. Click Test Connection to ensure that all the credentials are correct. This will be confirmed with the appearance of a message informing you about a successful test.
  7. Next, select Create Azure Blob Storage Connection.
  8. The new connection will appear in your list of connections.

Once you have completed the above, you can create a package and test it on the actual data stored in Azure Blob Storage.

If you want to modify any of the Azure Blob Storage connections in Xplenty, follow the steps listed below:

  1. Click your avatar at the top right of the screen and then select Manage Connections.
  2. Click a connection and then modify it or delete it. If you want to exit the edit Azure Blob Storage connection window without making any changes, just click connections at the top of the window.

As you can see from the above, what was once a tedious and complicated process can now be cut down to just a few easy steps with no coding.

Want to learn more about what you can do with Xplenty? Find out how all your data sources can be brought together with Xplenty to derive real business value.