2020 is finally over – and who’s not thankful for that? We most definitely are. Although 2020 was a total bummer ever since the COVID-19 outbreak, it was a great year for the SQLShack community. We’ve published a ton of great articles written by SQL Server professionals and community members.
We’d like to thank all of the authors for their contribution to spreading the knowledge around the SQL community. We couldn’t have done it without you all!
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In this article, we will explore how the ORDER BY statement affects the query performance and we will also learn some performance tips related to sorting operations in SQL Server.
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In this 4th article for the Amazon Aurora series, we will discuss and implement an Amazon Aurora Serverless cluster.
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After discussing a few algorithms and techniques and comparison of models with Azure Machine learning, let us discuss a validation technique, which is Cross-Validation in Azure Machine Learning in this article. During this series of articles, we have learned the basic cleaning techniques, feature selection techniques and Principal component analysis etc. After discussing Regression analysis, Classification analysis and comparing models, let us focus now on performing Cross-Validation in Azure Machine Learning in order to evaluate models.
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In the previous articles of this series, we showed how to create Azure Data Factory pipelines that consist of multiple activities to perform different actions, where the activities will be executed sequentially. This means that the next activity will not be executed until the previous activity is executed successfully without any issue.
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This article will help you create database objects in Azure Data Lake Analytics using U-SQL.
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In the previous article, How to schedule Azure Data Factory pipeline executions using Triggers, we discussed the three main types of the Azure Data Factory triggers, how to configure it then use it to schedule a pipeline.
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In this article, I am going to explain how to create a serverless application using Azure Functions and use Azure SQL Database to log messages generated by the function. In this world of cloud-based applications, it is very important that you are aware of how to create and design serverless applications. An important aspect while designing any application is to generate log messages at every key step or operation that is being performed. This helps us to understand the workflow whenever there are some issues and need debugging at some later point in time.
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In the two-part SQL Shack article, Build a Google BigQuery Resource, I showed how to build a Google BigQuery resource, and then link it to an Azure SQL Server resource. This article will expand on that first part, showing how to build a BigQuery report with Google Data Studio.
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In this article, we will explain how to install MongoDB on the Windows operating system, how to install and configure the ODBC driver and connector that allows us to import data from MongoDB to SQL Server using SSIS.
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Microsoft Power BI is a data analytics tool available in two flavors: Power BI Desktop and a Power BI Service.
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In this article, we are going to learn how we can develop a T-SQL script to update statistics of tables based on the row modification. It is always a challenging task to perform maintenance on a table that has billions of rows. During the early years of my professional career, I was assigned a project and one of our clients had performance issues. The initial analysis showed that due to frequent data modifications, a specific table’s statistics become outdated.
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In this article, we will explore the useful backtrack feature for Amazon Aurora clusters.
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You might be thinking why do you want to create Azure SQL Database and what are the best configurations. This article will provide you with the basic configurations of the Azure SQL Database.
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This article will help you learn to develop U-SQL jobs locally, which once ready, can be deployed on Azure Data Lake Analytics service on the Azure cloud.
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In this article, we will learn how to execute U-SQL jobs that have been developed or tested locally, to the production environment from a local machine.
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PowerShell becomes a de facto toolset in the arsenal of Azure automation. PowerShell provides a platform and a friendly way of automating many repeated tasks, which in turn minimize the time-and-cost. PowerShell always comes to the rescue when there is a need for automation, and it is no different for Azure. If you are already familiar with PowerShell cmdlets, then it will be easy to be acquainted with Azure PowerShell modules. For Azure automation, Microsoft provided a set of Azure PowerShell Modules that can be leverage to manage the Azure Cloud platform.
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In the previous articles, we discussed how to use the Azure Data Factory to move data between different data stores, how to transform data before writing it to a predefined sink, how to run an SSIS package using Azure Data Factory and how to use iterations and conditions activities in Azure Data Factory.
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In this article, we will guide you through tracking data changes on the Azure SQL database and introduce common use case scenarios and learn how to get the most out of system-versioned tables.
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In the article, Deploy your AWS RDS Aurora database clusters for MySQL, we explored the Amazon Aurora concept and deployment. In this article, we will understand about the global database feature and its implementations.
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In this article, we will learn how to develop U-SQL jobs on Azure Data Lake Analytics to process data stored in Data Lake Storage.
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Amazon offers managed database service for various database products such as Microsoft SQL Server, MySQL, PostgreSQL, Oracle. In these relational database services (RDS), AWS manages the operating system, networking components, backups, monitoring solutions. In the previous articles, we explored many useful RDS features under the AWS RDS category on SQLShack.
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In the previous articles, we discussed how to create an Azure Data Factory pipeline to copy data between different data stores that are located in on-premises servers or in the cloud, how to transform data using Azure Data factory Mapping Dataflow activity and how to run an SSIS package using Azure Data Factory.
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This article aims to help you understand the concept of Azure Data Lake Analytics capability offered by Microsoft in the Azure cloud.
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In this article, I am going to explain in detail about the SQL Server Agent service. This is a windows service that enables database developers and database administrators to schedule jobs on the SQL Server machine. The jobs can be simple T-SQL scripts, stored procedures, SSIS packages or SSAS databases. This service is available on all the editions of SQL Server except the Express edition.
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