Understanding the Process of an Azure Database Deployment on MySQL

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This article describes the step-by-step deployment process of the Azure Database for MySQL Server.

Open the Azure portal and log in using the appropriate credentials. Note: For demonstration purposes, I got a pay-as-you-go subscription to Microsoft Azure. For more information about the Azure price model and various Azure subscriptions, refer to Subscriptions, licenses, accounts, and tenants for Microsoft’s cloud offerings.

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Connecting to SQL Azure from SQL Server Management Studio (SSMS)

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Microsoft Azure is a cloud computing service for building, testing, deploying, and managing applications through the Microsoft data centers. It provides the Software as Service (SaaS), Platform as Service (PaaS), and Infrastructure as a Service (IaaS), and supports different database servers, programming languages, and tools.

Azure allows creating databases on various database server platforms, both open source and paid. The deployment is fast and scalable. Besides, the Azure license model is flexible, which helps to reduce the infrastructure costs.

The current article will highlight the following points:

  1. Create an Azure SQL Server instance.
  2. Connect to the Azure SQL Server using SQL Server Management Studio.
  3. Create an Azure SQL database using SQL Server Management Studio.
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Install Azure CLI 2.0 on Microsoft Windows

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Azure CLI is a Microsoft cross-platform tool that allows users to remotely access Azure services via their command line. The current article will describe installing Azure CLI 2.0 on Windows. However, before we go to perform this task, we’ll briefly review what Microsoft Azure is, what services it provides, and how to sign up with Microsoft Azure.

Let’s begin without ado.

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Introduction to Azure Database Migration Service (ADMS)

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Microsoft Azure platform provides an Azure Database Migration Service (ADMS) – a convenient solution for the Azure Cloud-based Databases migration tasks in a straight forward way. In this article, we elaborate on the AMDS essential work and integrated processes. 

We put in the focus issues related to the migration of object resources on Cloud to Cloud and on-premises database server to cloud. Also, we’ll deal with the cross-database migration compatibility between different database technologies.

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Developing Azure DevOps Extension

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Introduction

Azure DevOps Services provides a lot of space for importing your custom extension. Work items, pipeline tasks, dashboard widgets, and other options can serve this purpose.

This article will be about developing extensions for pipeline tasks – I will describe how to create the easiest sample extension that will help organize your own continuous integration.

But first, let’s describe the whole process of hosting the extension on Azure DevOps and how it works. Then we will discuss its detailed development route. Read More

How to install SQL Server vNext and Azure data studio on Ubuntu 18.04

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Azure data studio is a cross-platform database management tool. This tool is used to connect, configure, and administrate SQL Server instances installed locally or in the cloud. This tool can be installed on the following operating systems:

  1. Microsoft Windows
  2. Linux
    • Redgate
    • Debian
    • Ubuntu
  3. macOS

Initially, Microsoft introduced this tool as the “SQL Server operations studio.” Later they renamed it Azure Data Studio. You can get more information about it here.

In this article, I am going to explain the step-by-step installation process of SQL Server 2017 and Azure data studio on Ubuntu. I have divided the article into two parts. Firstly, we will install SQL Server 2017, and later I will explain the process of installing Azure Data Studio. For demonstration purposes, I have created a virtual machine and installed Ubuntu 18.04 on it. You can download Ubuntu here. Read More

Applying SQL Transformations and Handling Missing Values in Azure ML

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In this article, we will introduce SQL transformations in action. We will also see how to handle missing values in our dataset.

Consider a scenario of a movie rating dataset containing records of different movies along with the average user ratings associated with each movie. The ratings are in numeric form ranging from 1 to 10 with 1 as the lowest rating and, respectively, 10 as the highest rating (though no movie in the history has achieved 10 rating:). Suppose that we want to convert the numeric ratings into categorical ratings. For instance, we want to replace ratings of 1-3 with the categorical value “poor”, of 4-6 with “average” while ratings of 7-10 will have the value “good”. We can accomplish it with SQL transformation in Azure ML Studio. Read More

Microsoft Azure Vs Amazon Web Services: What’s your Ultimate Choice?

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Have you heard the term cloud computing? Do you wish to try your hands on cloud platforms? Well, if you seem to be a newbie to this new world of cloud computing, then set back as we are going to discuss the cloud platforms that are beneficial for generating more business. It’s vital for an individual to get themselves familiarize with different leading cloud service providers before selecting the best cloud network to begin their business or career with cloud computing.

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