Azure Synapse: The Ultimate Cloud-Based Analytics Solution for Data-Driven Organizations

As data becomes more and more critical to business success, organizations need powerful tools to process, manage, and analyze large volumes of data from various sources. This is where Azure Synapse comes in – a cloud-based analytics solution that enables organizations to derive insights from their data in real-time. In this blog post, we will explore what Azure Synapse is, how it works, and how it can benefit your organization.

What is Azure Synapse? Azure Synapse is a cloud-based analytics service that combines data warehousing and big data analytics into a single solution. It allows organizations to ingest, prepare, and manage large amounts of data from various sources, including structured, semi-structured, and unstructured data. With Azure Synapse, organizations can process data in real-time or batch mode and then analyze it using various tools and languages.

How does Azure Synapse work? Azure Synapse is built on top of Azure Data Lake Storage Gen2 and Azure SQL Data Warehouse. It provides a unified experience for data ingestion, data preparation, and data analysis. Here is an overview of how Azure Synapse works:

Data Ingestion: Azure Synapse allows organizations to ingest data from various sources, including Azure Blob Storage, Azure Data Lake Storage Gen2, and Azure Event Hubs. It also supports a wide range of data formats, including structured data from databases, semi-structured data from sources such as JSON or XML files, and unstructured data such as text, images, and videos.

Data Preparation: After ingesting data, organizations can prepare it for analysis using various tools such as Apache Spark, SQL Server, or Power Query. Azure Synapse provides a data preparation experience that allows users to clean, transform, and join data using a familiar SQL or Python-based language.

Data Analysis: Once the data is prepared, organizations can analyze it using various tools and languages, including Azure Machine Learning, R, Python, and Power BI. Azure Synapse integrates with these tools, making it easy to build end-to-end data pipelines that can handle large-scale data processing and analytics workloads.

Security: Azure Synapse provides advanced security features, including data encryption at rest and in transit, role-based access control, and auditing and compliance tools. These features help organizations maintain data privacy and security, which is critical in today’s data-driven world.

Benefits of Azure Synapse: Azure Synapse provides several benefits to organizations, including:

  1. Scalability: With Azure Synapse, organizations can easily scale their analytics workloads to handle large volumes of data. They can pay only for the resources they need, making it a cost-effective solution.
  2. Integration: Azure Synapse integrates with other Azure services such as Azure Data Factory, Azure Machine Learning, and Power BI, allowing organizations to build end-to-end data pipelines.
  3. Real-time analytics: Azure Synapse allows organizations to perform real-time analytics on streaming data, enabling them to make decisions based on the most up-to-date information.
  4. Simplified data management: Azure Synapse provides a unified experience for data ingestion, preparation, and analysis, simplifying the data management process for organizations.


Azure VM’s public direction

Each virtual machine we deploy in Azure, by default, has assigned a public IP, through which we can access it. You can later modify both access ports as restrict, in certain cases, public access.

IP and DNS of a virtual machine

To access the public IP of a virtual machine created in ARM model, open the panel of the machine from the list of virtual machines:


In the main panel the public IP appears, and if it was configured, your DNS. If the DNS appears undefined, you can specify one by clicking on the link:


In the Public IP panel, we can see the address and easily copy both IP and DNS.


If you click Settings, you will access to specific IP options. We can establish a static IP to the virtual machine (default is dynamic) and define a DNS domain within our geographic region domain:


Una vez guardados los cambios, en segundos que se habían aplicado y estarán a disposición del público.



Creating a Linux VM in Azure

Within the Azure marketplace we have multiple images ready to deploy. Among them are several distributions of Linux created by several companies, with several preinstalled packages if necessary.

Creating a Linux virtual machine

Let’s see the entire process of provisioning a virtual machine (IaaS) with an image of Canonical Ubuntu Server 15.10.

Step 1

We entered our Azure subscription and click on virtual machines:


Step 2

Click on add new virtual machine:


Step 3

We search and select the image Ubuntu Ubuntu Server 15.10 Canonical:


Step 4

The description of the VM image is showed, and we can choose whether we want in classic mode or resource manager. We will choose resource manager. You can see the differences on this link. Press create to start the process of provision:


Step 5

Now, you can fill the basic data of the virtual machine, with special attention to the geographical area of deployment and the resource group to which to assign. Select the location closest to where you want to give the service or one where you have all your virtual data center.

With regard to the resource group, remember that everything you bring inside will not restart simultaneously in the mantenimience operations, so its use is for high availability situations.

In this step you will define the root user and password, so please assure that the data is correct.

After filling all press accept.


Step 6

You must now select the size, which defines the cost of the machine. Choose the one you needed depending on the estimated use. The DS series, with SSDs are suitable for LAMP services for example.


Step 7

In this step you will configure additional options, such as network, storage type and others. When you finish, please press accept. If you do not yet know these concepts in Azure, the default options will be fine to start.


Step 8

A summary of the process is presented and a final confirmation is requested. If all is well, press accept and begin to supply the machine. If not, you can go back to correct it.

Creación VM Ubuntu

In the notification area you will have a notice of the process progress, as well in the main panel.

Once the deployment is complete, which may take about 5 to 10 minutes, you can connect via SSH with a client like Putty, using the public IP of the machine and against port 22, with root user that was defined in the basic options in step 5.

However this default setting is not the safest. In a next post we will see how to change the default ports and install a desktop for remote access. Later we will see how to configure the server to make a LAMP stack.