This stairway series was started in 2015. As such, the focus was on SQL Server 2012 and SQL Server 2014 only. When SQL Server 2016 was released, with lots of improvements in the columnstore technology, I decided to finish the planned levels with the original focus on SQL Server 2012 and 2014, and add one extra level with a brief overview of the improvements available in SQL Server 2016.
In this article we look at how to automate a SQL Server database restore using a PowerShell script.
Recently a customer asked me for help with setting up a test of an Azure SQL Database in the single database tier with Geo-Replication to work with Transparent Data Encryption (TDE) with a customer-managed key, also known as Bring Your Own Key (BYOK). It is very simple to do it when you use service-managed keys, […]
In this article we look at the incremental refresh feature when working with Power BI data sources and how to implement for your reports.
Today Steve looks at one possible future of offices, which might be something we own.
This article shows a basic Azure Data Factory pipeline to load data into Azure Synapse.
In this article, Diogo Souza explains GitFlow, a branching model for Git. He demonstrates how to work with GitFlow to create and deploy a feature and a hotfix to GitHub.
In this article we look at the incremental refresh feature when working with Power BI data sources and how to implement for your reports.
There are plenty of experts that look to teach you about query tuning and the internals of query execution in SQL Server.
Every organization I talk to has the same problem dressed up in different clothes....
By DataOnWheels
I am delighted to host this month’s T-SQL Tuesday invitation. If you are new...
By alevyinroc
Ten years (and a couple jobs) ago, I wrote about naming default constraints to...
Comments posted to this topic are about the item The day-to-day pressures of a...
Comments posted to this topic are about the item Using OPENJSON
Comments posted to this topic are about the item Data Modeling with dbt for...
I have some data in a table that looks like this:
BeerID BeerName brewer beerdescription 1 Becks Interbrew Beck's is a German-style pilsner beer 2 Fat Tire New Belgium Toasty malt, gentle sweetness, flash of fresh hop bitterness. 3 Mac n Jacks Mac & Jack's Brewery This beer erupts with a floral, hoppy taste 4 Alaskan Amber Alaskan Brewing Alaskan Brewing Amber Ale is an "alt" style beer 8 Kirin Kirin Brewing Kirin Ichiban is a Lager-type beerIf I run this, what is returned?
select t1.key
from openjson((select t.* FROM Beer AS t for json path)) t1 See possible answers