In the previous article Azure Data Explorer and the Kusto Query Language, we saw how the Microsoft Azure Data Explorer works, and we learned about the Kusto query language (KQL). We’ll build on this here in part two, we’ll learn more about KQL, and we’ll use KQL to solve a real-world data problem.
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As we are well into the discussions of Text Analytics in Azure Machine Learning from the last couple of articles, we will be discussing the Filter based Feature Selection in Text Analytics and how we can build a prediction model from the Filter Based Feature Selection in order to perform text classification.
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This article will restore a Transparent Data Encrypted Azure SQL Database into an on-premise SQL Server. Further, we will also create a copy of the Azure database on the same server.
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This article will show how to source data from Azure SQL Database into Azure Machine Learning.
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This article is a part of the series – Learn NoSQL in Azure where we explore Azure Cosmos DB as a part of the non-relational database system used widely for a variety of applications. Azure Cosmos DB is a part of Microsoft’s serverless databases on Azure which is highly scalable and distributed across all locations that run on Azure. It is offered as a platform as a service (PAAS) from Azure and you can develop databases that have a very high throughput and very low latency. Using Azure Cosmos DB, customers can replicate their data across multiple locations across the globe and also across multiple locations within the same region. This makes Cosmos DB a highly available database service with almost 99.999% availability for reads and writes for multi-region modes and almost 99.99% availability for single-region modes.
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Azure SQL Database is a Platform-as-a-Service (PaaS) solution that offers managed database service. Azure DB provides many features such as automatic database tuning, vulnerability assessment, automated patching, performance tuning, alerts. It provides a 99.995% availability SLA for the Zone redundant database in the business-critical service tier.
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This article will walk you through creating a new SQL pool within an existing Azure SQL Server as well as catalog the same using the Azure Purview service.
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This article explores the recently announced preview feature of Azure SQL Database – Query Store Hints.
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Microsoft Azure Data Explorer handles and analyzes petabyte-masses of structured and unstructured data. In Azure Data Explorer, users lever the Kusto query language (KQL) for their data analysis work. This article, part one of a two-part article, will introduce KQL. This article will also describe a free Microsoft online interactive resource that allows for hands-on Kusto exploration and learning. Part two will describe more aspects of KQL, and use those aspects to solve a real-world data problem.
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In this article, we are going to learn Azure Cosmos DB. This article is a part of the series Learn NoSQL in Azure, where we will explore all the different types of non-relational databases that are supported in Azure at the moment. Azure is one of the most popular public cloud platforms that has a big market share all over the world. Cosmos DB is a part of the Databases section in Azure that allows customers to create and use NoSQL or non-relational databases and consume these at scale. You can leverage Cosmos DB to build highly scalable and robust cloud-based applications that support modern big data workloads. Let us understand more about what a NoSQL database is all about and how it is different from a relational database. Although this article focuses on the NoSQL related to Azure, it is to be known that other open-source projects support NoSQL databases like Apache Cassandra, etc. However, these topics are out of the scope of this article and we will focus on Azure mostly.
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Today, we will implement an Azure Logic App for face recognition and insert its data into an Azure SQL database.
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In this article, we will learn how to integrate Azure Purview and Azure Synapse Analytics capabilities to access data catalog assets hosted in Purview from Azure Synapse.
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Suppose you write a technical blog in the English language for your website. You have good followers in a country where the primary language is not English. You want to translate the document content in their native language for a wider reach.
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This article talks about the steps required to add and use the DB Snapshot Creator extension in Azure Data Studio.
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In this article, we will learn how to configure Azure Purview to catalog data hosted in AWS S3.
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This article uses Azure automation techniques for sending query results as a CSV file attachment in Azure SQL Database by using Azure logic apps.
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In this article, we will show how to connect to instances of Azure Database for PostgreSQL servers using the pgAdmin tool installed locally on a user’s workstation.
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This article implements Azure Automation logic for automatically publishing a LinkedIn post and Twitter’s Tweet using the simplified Azure Logic App.
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In this article, we will look briefly at the Azure Cosmos DB service and how you can query JSON documents to store, retrieve and process data using the SQL Application Programming Interface (API).
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This article is all about declarative database development using Azure Data Studio for both beginners and professionals who are new to it.
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This article uses Azure Automation techniques to import data into Azure SQL Database from Azure Storage container.
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This article will walk you through the process to optimize the cost of Azure Database for PostgreSQL.
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This article configures Azure Automation for Analyzing Twitter sentiments using Azure Logic Apps and stores them into Azure SQL Database.
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After starting our discussions into Text Analytics in Azure Machine Learning from the last article, we will be discussing the Named Entity Recognition control in Azure Machine Learning in this article.
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This article will get you started with Azure Database for PostgreSQL and understand various options offered by this.
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