Introduction JSON (JavaScript Object Notation) has become a popular data format for storing and exchanging information. Microsoft SQL Server, starting from version 2016, introduced built-in support for JSON, allowing developers to work with JSON data more efficiently within the relational database environment. This article will explore how to store, retrieve, and manipulate JSON data in […]
There may come a time when you want to or need to rename a database. In this tip we look at a couple different options.
Linked servers in Amazon RDS for SQL Server allow seamless connectivity to remote databases for distributed queries and data integration. In this article, I guide you through the step-by-step process of creating a linked server using SQL commands, from setting up authentication to testing the connection. Learn best practices, advanced configurations, and essential considerations, including why you can't use SSMS for linked server setup in RDS. This professional guide is tailored for experienced database administrators looking to optimize cross-server operations.
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Key vaults define security boundaries for stored secrets. It allows you to securely store service or application credentials like passwords and access keys as secrets. All secrets in your key vault are encrypted with a software key. When you use Key Vault, you no longer need to store security information in your applications. Not having to store security information in applications eliminates the need to make this information part of the code.
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Date manipulation is a common scenario when retrieving or storing data in a Microsoft SQL Server database. There are several date functions (DATENAME, DATEPART, DATEADD, DATEDIFF, etc.) that are available and in this tutorial, we look at how to use the DATEADD function in SQL queries, stored procedures, T-SQL scripts, etc. for OLTP databases as well as data warehouse and data science projects.
In my family’s history of the past 10+ years, we have become well versed in nagging, ongoing, non-debilitating pain. In some ways, the lessons we have learned about physical pain correlate all too well to the types of pain that we technical people are involved with daily. But there is a huge difference, even if […]
Poor data quality significantly hinders large enterprises from deriving meaningful value. The variety of data is a crucial factor to account for when assessing & rectifying data quality, as diverse data types introduce unique challenges in maintaining accuracy and consistency. Good data quality and integrity are essential for accurate insights, good decision-making, and potential success of large enterprises. Inconsistent, incomplete, and inaccurate data significantly affect business operations, customer satisfaction, and financial performance. SQL provides robust functions to proactively identify and resolve these data quality issues, ensuring accurate, reliable, and consistent data for reporting and analysis.
Steve has a few thoughts on becoming more effective. This involves more than just becoming a better coder.
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I have this data in a table called dbo.NFLTeams
TeamID TeamName City YearEstablished ------ -------- ---- --------------- 1 Cowboys Dallas 1960 2 Eagles Philadelphia 1933 3 Packers Green Bay 1919 4 Chiefs Kansas City 1960 5 49ers San Francisco 1946 6 Broncos Denver 1960 7 Seahawks Seattle 1976 8 Patriots New England 1960If I run this code, how many rows are returned?
SELECT TOP 2
json_objectagg('Team' : TeamName)
FROM dbo.NFLTeams;
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