Tag: azure

Applying SQL Transformations and Handling Missing Values in Azure ML

Ben Richardson
Total: 1 Average: 5

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 Graph or Azure Active Directory Graph API: Which is better?

Kibo Hutchinson
Total: 1 Average: 4

Are you a .NET developer who is stuck in great confusion when it comes to choosing Azure Active Directory or Microsoft Graph?

We all have look at those multiple posts on which you can choose for better web development. In this article, we will be providing some guidance along with a bit of roadmap to clarify things for all of the existing and new developers who want to access directory-based features. Let us begin. Read More

How to Test Azure Web Application Performance through Microsoft Azure and Visual Studio

Amarendra Babu
Total: 27 Average: 4.2

Before deploying your application into production, doing a performance load test is imperative for measuring future performance and ensure that your application is production-ready.

Testing is essential for every application to make sure that any application works and performs according to the desired requirements. During the application testing process, we can attempt and find out if any imperfections are remaining in the application. There are numerous sorts of testing like functional testing, unit testing, acceptance testing, and integration testing. We compose Functional and UI tests to see whether the application is working as per the requirements. Read More

Azure Cosmos DB Analysis

Kiran Gutha
Total: 4 Average: 3.3

Azure Cosmos DB is the first globally distributed, multi-model database service for building world-scale applications. Over the years, it has been providing momentum for Microsoft’s Internet-scale services, which are now available to all Azure developers. The service is designed to allow customers to flexibly and horizontally scale throughput and storage across any number of geographic regions. Read More

Getting Started with SQL Server 2017 on Linux in the Azure portal

Prashanth Jayaram
Total: 9 Average: 3.8

SQL Server 2017 now is considered as a hybrid database enterprise solution as it expands its market and is ported to other operating system platforms. It also includes mainstream support for Linux machines. The Cloud makes the life of administrator much easier, now it’s no longer daunting task to configure the SQL Server instance. The easiest way to explore SQL Server on Linux is to provision a virtual machine through Microsoft Azure portal – portal.azure.com. The Linux azure virtual machine will come pre-configured with Linux and SQL Server 2017.

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Creating Simple Linear Regression in Azure Machine Learning

Esat Erkeç
Total: 3 Average: 4

In today’s world, it is not enough to simply analyze data, create reports or develop business intelligence projects. To discover the power of data, we have to modify data on machine learning models and to predict future.

In this article, we will discuss one of the simplest methods, a linear regression, that we are going to modify statically in Azure Machine Learning.

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Upload Documents to Azure Data Lake and Export Data using SSIS

Daniel Calbimonte
Total: 3 Average: 3.7

 Introduction

Azure is growing every day. Microsoft created Azure, which is a Cloud Computing service released on 2010.

According to Microsoft, 80% of the fortune 500 companies are using Azure. Also, 40% of the Azure Revenue comes from Startups and independent software vendors. 33% of the Azure Virtual Machines are using Linux. Microsoft expects to earn $20 billion in 2018.

That is why companies are migrating part of the data to Azure and sometimes all the data.

Azure Data Lake is a special storage to analyze Big Data in parallel in Azure. It is optimized for analytics. You can store Social network data, emails, documents, sensor information, geographical information and more.

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Working with SQL Server in Hybrid Cloud Scenarios. Part 2

Alexey Shulenin
Total: 4 Average: 2.8

As a rule, impersonal information is stored in a public cloud, and the personalized part – in a private cloud. The question thus arises – how to combine both parts to return a single result at a user’s request? Suppose there is a table of customers divided vertically. The depersonalized columns were included in the table located in Windows Azure SQL Database, and columns with sensitive information (e.g., full name) remained in the local SQL Server. Both tables must be linked by the CustomerID key. Because they are located in different databases on different servers, the JOIN statement will not work. As a possible solution, we have considered the scenario, when the linkage was implemented on the local SQL Server. It served as a kind of entry point for the applications, and the cloud-based SQL Server was set up on it as a linked server. In this article, we will consider the case when both, the local and cloud servers, are equal in terms of the application, and the data merging occurs directly in it, i.e. at the business logic level.

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Working with SQL Server in Hybrid Cloud Scenarios

Alexey Shulenin
Total: 4 Average: 3

A hybrid cloud is a fairly attractive model when implementing cloud computing in enterprise information systems since this approach combines the advantages of public and private clouds. On the one hand, it is possible to flexibly attract external resources when needed and reduce infrastructure costs. On the other hand, full control over data and applications that the enterprise does not want to outsource remains. However, in such a scenario, we inevitably face the task of integrating data from various sources. Suppose there is a table with customers, which is vertically divided into two parts. The depersonalized part was allocated in a public cloud, and the information personalizing the customers remained in a local database. For holistic processing inside the application, you need to combine both parts by CustomerID. There are various ways to do this. Conventionally, they can be divided into two large categories: data aggregation at the on-premise database server level which, in this case, will be a single sign on for accessing local and remote data, and data aggregation within the business logic. This article will consider the first approach.

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Azure SSAS. Cubes in Clouds

Eugene Polonichko
Total: 3 Average: 2.7

Autumn of 2016 was full of events from Microsoft dedicated to analytics. In practice, the company began aggressive promotion of its predictive analytics and BI platform in the cloud. Finally, it has happened – Microsoft has released the preview of Azure SSAS Tabular. In fact, the company has transferred SSAS Tabular to the cloud. Therefore, SQL Server Analysis Enterprise Edition in cloud  supports DirectQuery, partitions, row-level security, bi-directional relationships, and has compatibility level 1200.

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