Many people ask me how to get the Microsoft SQL Certification. SQL Server has a lot of certifications and specializations. In this article, we will provide an introduction to each of them and provide some tips related. At the time of this publication, we are under the Coronavirus era. Many people are at home with free time. Instead of watching all the bad COVID 19 news, it is a great idea to earn a new certification.
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In my previous article, Learn MySQL: Sorting and Filtering data in a table, we had learned about the sorting and filtering of the data using WHERE and ORDER BY clause.
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In this article, we are going to learn how we can back up the SQL database to Azure using a database maintenance plan. To demonstrate the process, I have restored the AdventureWorks2017 database on my workstation. I have created an Azure container named sqlbackups in my storage account.
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In this article, you will learn how to work with Treemaps and Tables, which are two of the most commonly used Power BI visuals. You will also see how slicers can be used in Power BI to dynamically update the data in Treemaps and Tables. Power BI Visuals are extremely easy to create and don’t require you to write any code.
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In this article, I am going to explain how to use Pandas in Python. Pandas is one of the most popular modules in python that can be used for data manipulation and analysis using python. Basically, it provides an easy interface to interact with flowing data and apply transformations to them on the go. This module is covered under the BSD license and can be used for free. You can download this module by visiting the website or by installing it through the python package manager.
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This is the 9th article in the series of SQL Server Always On Availability Groups.
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In this article, I am going to explain ODBC drivers. We will go through the process to set up the ODBC driver for MySQL and use it to create an SSRS report. First, let me talk about ODBC drivers.
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In the previous two trips of this articles series, databases trip to SQL Server on Azure VM and to Azure SQL Database, we discussed the benefits of migrating your on-premises SQL Server databases to the Microsoft Azure database platforms and the methods that can be followed to migrate the on-premises databases to the Azure database platforms.
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Recently, we have received a strange request from our customer. They want us to set up a schedule a backup job that generates a backup of SQL database, compress the backup file in multiple compressed archive files (WinRAR files.) We tried to explain to the customer that the SQL Server native backups are capable of compressing the backup file, and it can split a large and compressed backup into multiple backup files. But they insisted us to use the WinRAR software to compress and split the backup.
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Having discussed different aspects of MDM SSAS cubes, we will look at the Microsoft recommended OLAP tool, SSAS Tabular Models for data analytics. There are a few advantages of using Tabular Models over MDM that are listed below.
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In the previously published article, Getting started with Sphinx search engine, we talked about the Sphinx search engine and how to install it on the Windows operating system. In this article, we will talk about building full-text indexes using Sphinx. We will be covering seven topics:
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In the previous article of this series, Migrate SQL workloads to Microsoft Azure: Databases trip to SQL Server on Azure VM, we went through the methods that can be used for assessing your on-premises SQL Server databases before the migration process then migrating it to a SQL Server instance hosted in a Microsoft Azure VM.
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Microsoft Azure offers hundreds of cloud products, with more on the way. In the database space, Microsoft offers Azure Cosmos DB, a NoSQL database product. We can build Java, .Net, etc. applications around Cosmos DB resources. To extend this capability, this article will show how to query Cosmos DB directly from SQL Server.
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This article provides a step by step explanation of how to share AWS Redshift database snapshots with other AWS accounts to enable porting of data from one AWS account to another.
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This article gives an overview of configuring AWS Redshift snapshots for scheduled data backup, data archival, as well as disaster recovery.
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In the previous articles of this series, we built the bridge that leads us to the best way of migrating our SQL workload to Microsoft Azure, by showing how to create the databases migration strategy that contains a deep study of the current environment and the available options in Azure to replace the on-premises setup, which we tried to make it easier by providing all Azure database services and the workload that fits each service, and finally, we introduced several Microsoft tools and services that can be used to assess the current setup, provide migration guidance steps and migrate the databases to Microsoft Azure services with the minimal downtime.
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In this article, I am going to explain what Amazon S3 is and how to connect to it using python. This article will be focused on beginners who are trying to get their hands on in python and working around the AWS ecosystem. AWS, as you might know, is one of the largest cloud providers along with Microsoft Azure and Google Cloud Platform. There are a lot of services offered by Amazon including AWS S3. Amazon S3, also abbreviated as Amazon Simple Storage Service is a storage service offered by the cloud provider that enables the users to store any kind of files in this service. It is designed to make web-scale computing easier for developers.
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In the previous articles of this series we discussed how to draw the initial strategy when planning to migrate the SQL workload to Microsoft Azure, the different database target platforms provided by Microsoft Azure that can be used as a migration target, based on the workload type, and finally, we went through some tools that help in discovering and assessing the on-premises environment by identifying the migration blocking issues and providing guidance steps for the migration process.
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In this article, I am going to introduce the Tabular Object Model (TOM) in the Power BI Data Model and provide an understanding of how this model can be accessed outside of the Power BI environment. For the sake of this tutorial, we are going to use the Visual Studio Code to simply write a dotnet console application and try to access the Tabular Object Model from the Power BI file. With the help of this knowledge, programmers and BI developers can not only view the underlying model in the Power BI Data Model but also can enhance the data model programmatically by writing a few lines of code. It can also be further improved by automating the creation of the Power BI models with the help of the Tabular Object Model library in dotnet.
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In the previous articles, Migrating SQL workloads to Microsoft Azure: Planning the jump and Migrating SQL workloads to Microsoft Azure: Services Selection, we discussed the steps that you should follow when you start thinking loudly that you need to migrate your SQL workload to Azure, by checking your on-prem site and the available services and features in Azure that meet your workload handling requirements. After that, we went through different database services provided by Azure and which one fits a specific workload, in order to make it easy for you to translate the current workload as an Azure service.
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This is the 8th article in the series for SQL Server Always On Availability Groups.
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In this article, I am going to explain how we can split the large backup file into multiple small backup files using SSMS 2016. I will also explain how we can combine multiple backups to restore a database and split the backup of the SQL database using SQL Server Management Studio (SSMS).
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This is the 7th article in the series of SQL Server Always on Availability Groups.
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This article gives an overview of configuring the redshift cluster to access AWS S3 as well as loading data into AWS Redshift.
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Using Azure SQL Analytics, you will rediscover the new ways to manage the Azure SQL Database. Microsoft is driving an intelligent platform to provide seamless collaboration for all their end users to business analysts, by building an effective Log Analytics stack and intelligent insight through dashboards.
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