Today, data is the basis of any business. The world of enterprise computing is the epitome of data-driven businesses. The importance of structured storage of data is unquestionably in the focus. And at this time, with the computing model quickly shifting towards the cloud, and storage costs falling rapidly, enterprises are leveraging data more and more to tune their businesses.
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SQL has many cool features and aggregate functions are definitely one of these features, actually functions. While they are not specific to SQL, they are used often. They are part of the SELECT statement, and this allows us to have all benefits of SELECT (joining tables, filtering only rows and columns we need), combined with the power of these functions.
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Association Rule Mining in SQL Server is the next article in our data mining article series in which we have discussed Naïve Bayes, Decision Trees, and Time Series until now. Association Rule Mining, also known as Market Basket Analysis, mainly because Association Mining is used to find out the items which are bought together by the customers during their shopping.
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SQL join multiple tables is one of the most popular types of statements executed while handling relational databases. As known, there are five types of join operations: Inner, Left, Right, Full and Cross joins.
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SQL Server collation refers to a set of character and character encoding rules, and influences how information is stored according to the order in the data page, how data is matched by comparing two columns, and how information is arranged in the T-SQL query statement. Collate SQL follows rules applied on a table when Select, Insert, Update or Delete operations are performed against contained data. Data always follows collation constraint rules, which are configured when creating an object.
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If you want to get something meaningful out of data, you’ll almost always need to join multiple tables. In this article, we’ll show how to do that using different types of joins. To achieve that, we’ll combine INNER JOINs and LEFT JOINs. So, let’s start.
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In this article, we’ll show how to create an XML data type document from a relational table utilizing different T-SQL ways. For example, for data migration, information from the SQL Server database can be exported and imported using XML in another framework. XML is a standard way of extracting, storing and manipulating data. One aspect of working with the XML data type is creating XML from relational information, which is done using the FOR XML provision in SQL Server:
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Microsoft SQL Server Server Management is an advanced development environment that enables us to configure, manage and administrate SQL Server database engines. SSMS is very popular and widely used by the database developers and administrators because of the following advantages:
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Power BI is enriched with many useful visualizations and helps to represent data in various forms. We have explored many use cases of PowerBI in SQLShack articles.
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In this article, we are going to see how to use the CREATE VIEW SQL statement to create a view. This is the first article in a series that will be a programmatical approach of creating, altering and working with views using T-SQL. If you are a beginner and you don’t even know what a view is, don’t worry. We will kick off with a definition, and then move on to some basics like syntax, examples, use cases, etc.
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XQuery is a query language for XML. XML is a markup language that provides software and hardware-independent way of storing, transporting, and sharing data. In this case, XML documents are stored in a SQL Server database. XQuery is used to manipulate, find and extract information stored in the XML format. It’s analogous to SQL for databases.
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This article explores estimating the AWS RDS SQL Server cost so that you can plan resources accordingly.
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SQL cursor is one of the most popular database objects. It is used to retrieve data from the result set of an SQL query one row at a time. Even if the cursor is not recommended from a performance perspective, they are still widely used especially when handling a small amount of data.
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One of the most important things in databases is to understand the types of relations in the databases. That stands for both – a process of designing a database model as well as when you’re analyzing your data. Understanding these relations is somehow natural and not so complex but is still essential in the database theory (and practice).
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In this article, I am going to explain step by step process to perform Database Mail configuration in SQL Server Express edition using the T-SQL script. As we know, SQL Server Express edition does not provide the SQL Server Agent Services; hence we cannot perform Database Mail configuration or SQL Jobs or maintenance plans using SQL Server Management Studio. To configure the Database Mail feature in the SQL Server Express edition, we must use CLR integration or using stored procedures within the MSDB database.
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In this article, we will describe the relation between the Set Theory and SQL Server Set Operations
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I can hardly imagine making any complex database changes without using SQL scripts. We actually used them in this series so far, but we haven’t pointed out what they actually are. Today we’ll stand up against that injustice. Sit back, relax, and get ready to learn something new and useful.
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In this article, I am going to explain how we can use the SQL Server Express edition for the SQL witness server of the database mirroring setup. Database mirroring is a cost-effective and easy to configure high availability solution. Unfortunately, this feature has been deprecated, but still, some organizations use database mirroring as a high availability solution.
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This article explores the server and database audit in AWS RDS SQL Server.
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In this article, I am going to explain how to install the SQL Server Express edition. We will download the SQL Server 2017 Express edition and perform the custom installation. Before we dive-in into the installation and configuration process, let me introduce you to the SQL Server Express edition.
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This article explores the process of JSON data import in the SQL Server table using T-SQL and SSIS.
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This article installs PostgreSQL on Ubuntu 16.4 operating system and connects the database using Azure Data Studio.
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INNER JOIN vs LEFT JOIN, that is the question. Today, we’ll briefly explain how both of these two join types are used and what is the difference. We’ll go through this topic again later when we’ll expand our model and be able to write much more complex queries.
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This article gives an introduction of the non-clustered index in SQL Server using examples.
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SQL Express is a free and feature-limited edition of SQL Server that has been being published since the SQL Server 2005 version and it still continues to be published by Microsoft. Nowadays, Microsoft has released the Express edition of SQL Server 2019. We can use this edition for lightweight data-driven mobile, desktop or web applications. However, when we decide to use this edition, the supported features have to be checked in the Editions and supported features of SQL Server 2019. For example, the database size can not exceed 10 GB and the SQL Server Agent feature is not supported by the Express editions. As a result, we must take the limited features into consideration before planning to use the SQL Express Editions.
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