A Fine Slice Of SQL Server
Steven Sanderson performs a pattern match:
In R, finding patterns in text is a common task, and one of the most powerful functions to do this is
grep(). This function is used to search for patterns in strings, allowing you to locate elements that match a specific pattern. Today, we’ll explore how to use wildcard characters withgrep()to enhance your string searching capabilities. Let’s dive in!
Read on to learn more about how to use the grep() function.
Andy Brownsword lets things get out of hand:
Last week we looked at using Database Snapshots to help with rolling back upgrades. The snapshot maintained a point in time copy of the database which could be later restored.
We can go further – a database can have multiple snapshots.
Let’s suppose we want to take one before an upgrade, another once the upgrade is complete, and another before the start of business the following day. This would provide us multiple points to restore too.
This however makes restoring more complicated.
My recollection is that it’s not just restoration that gets more complicated, but also any database activity, to the point where too many database snapshots on a single database can have a considerable performance impact.
Comments closedElena Drakulevska builds a map:
Are you aiming for that WOW effect when your client opens your report? I’ve found that people often experience an immediate sense of awe when they see a map visual, especially when it’s conditionally formatted to highlight, for example, which country has the highest sales. So, I thought I’d share how you can achieve this and go beyond the built-in shape maps in Power BI. Let’s transform your global data into compelling visual stories!
Click through to learn more about the technique.
Comments closedSandeep Pawar sets up a default lakehouse:
I wrote a blog post a while ago on mounting a lakehouse (or generally speaking a storage location) to all nodes in a Fabric spark notebook. This allows you to use the File API file path from the mounted lakehouse.
Mounting a lakehouse using
mssparkutils.fs.mount()doesn’t define the default lakehouse of a notebook. To do so, you can use the configure magic as below:
Read on for that command, as well as some notes around using it.
Comments closedMarco Russo announces an updated product:
I am proud to announce the second version of the Contoso Data Generator!
In January 2022, we released the first version of an open-source project to create a sample relational database for semantic models in Power BI and Analysis Services. That version focused on creating a SQL Server database as a starting point for the semantic model.We invested in a new version to support more scenarios and products! Yes, Power BI is our primary focus, but 90% of our work could have been helpful for other platforms and architectures, so… why not?
Read on to see how you can use this and generate as much data as you want.
Comments closedJosephine Bush creates and uses a managed identity:
Benefits of Using Managed Identities and Entra Groups
- Enhanced Security: Using managed identities eliminates the need to manage credentials, reducing the risk of credential theft.
- Simplified Management: Entra Groups streamline the management of permissions for multiple users or managed identities, making it easier to apply consistent access policies.
- Scalability: As your organization grows, you can easily manage access by adding new users or managed identities to Entra Groups without needing to update database permissions individually.
Read on to see how you can create one and what you can do with it.
Comments closed