Exploring SQL Server 2016 Always Encrypted – Part 4 – Encrypting Existing Data
Greg Larsen explores the different ways that you can encrypt your existing confidential data using Always Encrypted Columns in SQL Server 2016.
Greg Larsen explores the different ways that you can encrypt your existing confidential data using Always Encrypted Columns in SQL Server 2016.
This article gives an overview of the Microsoft Azure SQL Data Warehouse architecture. The new platform-as-a service (PaaS) offering provides independent compute and storage scaling on demand and is currently in public preview.
An explanation as to what Log Shipping is and why it's still a viable solution in 2016.
The whole point of using a cloud service is to be able to use it intensively for a brief period just when it is needed and then clear out all your work when you've finished. This means automation to make the process as quick and easy as possible. It is likely to mean creating a VM, provisioning it from scratch and spinning it up using PowerShell. Relax, grab the popcorn, and let Adam Bertram show you how he does it in Azure.
Passwords are always a challenge, but are bad passwords the users' fault? Steve Jones has a few thoughts.
Arshad Ali demonstrates what the APPLY operator is, how it differs from regular JOINs, and what its applications are.
Steve Jones talks version control, but from the production perspective.
Traditional deployments of Azure SQL Database involve identifying projected resource requirements and selecting individual Azure SQL Database instances. For fluctuating workloads, this frequently results in over- or under-provisioning. To address this challenge, Microsoft offers another approach to sizing Azure SQL Database that relies on Elastic Database Pools. Marcin Policht takes a look.
Someone made a call to architect zero downtime for databases. Steve Jones isn't sure this is the best thing you could do.
You can develop a Power BI Dashboard that uses an R machine learning script as its data source and custom visuals. Here is a simple example that shows how to connect to data sources over the Internet, cleanse, transform and enrich the data through the use analytical datasets returned by the R script, design the dashboard and finally share it.
Do you know if your SQL Server is really running at its best? To...
You can find the slides of my session on the €100 DWH in Azure...
By Steve Jones
This value is something that I still hear today: our best work is done...
Hi everyone I am writing an SP where there is logic inside the SP...
Comments posted to this topic are about the item Planning for tomorrow, today -...
We have a BI-application that connects to input tables on a SQL Server 2022...
I try to run this code on SQL Server 2022. All the objects exist in the database.
CREATE OR ALTER VIEW OrderShipping AS SELECT cl.CityNameID, cl.CityName, o.OrderID, o.Customer, o.OrderDate, o.CustomerID, o.cityId FROM dbo.CityList AS cl INNER JOIN dbo.[Order] AS o ON o.cityId = cl.CityNameID GO CREATE OR ALTER FUNCTION GetShipCityForOrder ( @OrderID INT ) RETURNS VARCHAR(50) WITH SCHEMABINDING AS BEGIN DECLARE @city VARCHAR(50); SELECT @city = os.CityName FROM dbo.OrderShipping AS os WHERE os.OrderID = @OrderID; RETURN @city; END; goWhat is the result? See possible answers