A Fine Slice Of SQL Server
Tomaz Kastrun takes a peek at the Azure AI Services Language and Translation UI:
In Language + Translation UI you will give you capabilities to integrate the natural languages into your apps, bots and other services. With Language + Transport you can redact sensitive data, segment your text, and many more.
Click through for a demonstration.
Leave a CommentRob Farley cashed in all of his chips and got something nice out of it:
I had written to Santa (okay, the product group at Microsoft) to ask for this. It wasn’t quite “If I’m on the nice list, what I’d like is a unicorn train set”, but more like “If it’s not too much trouble, this thing here would be amazing…”
The thing was the ability to see the “number of rows read” by an Index Seek operation in a SQL plan containing the “Actuals” (post-execution).
Read on for information about why this is so useful.
Leave a CommentHugo Kornelis looks back at some nice additions to SQL Server:
It’s December. The last month of the year, and hence also the last T-SQL Tuesday of the year. Edition 181 is hosted by Kevin Chant. His chosen topic for this episode is to have us talk about which SQL Server announcement excited us the most.
This posed a bit of a problem for me. The only truthful answer here is that I have never been as excited about an announced new feature as when the Query Store was announced. But I also realized that I don’t have much to write about the Query Store, except how awesome it is. Okay, I could go on a full explanation, but many others do that much better, and have already done so. So that doesn’t leave much for me.
And that’s why I’ll also include my second favorite announcement.
Read on for a little bit around Query Store, followed up with coverage of several interesting additions to SQL Server over the years.
Leave a CommentIn this video, I show how to back up and restore SQL Server databases in piecemeal form, using filegroups to manage read-only versus read-write data, and bringing the most important data back online sooner in a recovery scenario.
I found the process to be a bit trickier than I had first expected, so I’m hoping this video has enough legs to prevent others from running into some of the problems I experienced.
Leave a CommentWhen building products that interact with multiple database platforms, the complexity can be both a challenge and an opportunity. For Subject Matter Experts (SMEs), observing design decisions made without sufficient knowledge of underlying database architecture can be particularly frustrating. These moments highlight the critical need for architectural foresight and platform-specific expertise to avoid pitfalls that compromise scalability, performance, and maintainability.
Read on for a list of common problems as well as the entry point to some solutions.
Leave a CommentPatrick Keisler notes an interesting data capture result:
Several months ago, I discussed my customer’s intention to enable trace flag 3625. Since that time, we have observed an intriguing phenomenon when encountering a login failure.
To demonstrate this, our initial step is to ensure we are capturing failed login attempts. In Server Properties, select the Security tab, click on Failed Logins Only, and then click OK.
Patrick has a link to a description of trace flag 3625, but the short version is that it masks sensitive information in error messages from non-sysadmins.
Leave a CommentAndy Brownsword gets into the spirit:
Reviewing performance for a SQL database over time can be a challenge without hand crafted tooling or using external monitoring apps. This isn’t about putting fires out, we’re looking at proactive monitoring and taking action for incremental improvements.
The Query Store comes to the rescue by providing built-in insights into key performance metrics over time. We can use different combinations of them to better understand how the database is working.
Query Store isn’t perfect, but it’s very good solution to an extremely common problem.
Leave a CommentDeepthi Goguri is pleased with a new spin on an existing product:
“SQL database in Microsoft Fabric is a developer-friendly transactional database, based on Azure SQL Database, that allows you to easily create your operational database in Fabric. A SQL database in Fabric uses the same SQL Database Engine as Azure SQL Database.”
As you read, this is a transactional database that can be created in fabric and can be replicated to Data Lake for the analytical workloads. The other main goal is to help build AI apps faster using the SQL Databases in Fabric. The data is replicated in near real time and converted to Parquet, in an analytics-ready format.
Read on to learn more about the offering. I’m still not 100% sold on its virtues versus simply having an Azure SQL Database and enabling mirroring.
Leave a CommentTomaz Kastrun writes some code:
Besides Python Speech SKD there are multiple languages supported with Speech SDK. Python SDK will expose you many of the Speech service capabilities for developing speech-enabled applications. Ideal for scenarios for (near) real-time and non real-time cases by using other Azure services as storage, streams and analytics
Click through for a demonstration.
Leave a CommentSteven Sanderson finds the column with the maximum value for each row in an R data frame:
Finding the column with the maximum value for each row is a useful operation when you want to identify the dominant category, highest measurement, or most significant feature in your dataset. This can provide valuable insights and help in decision-making processes.
R offers several ways to accomplish this task, ranging from base R functions to powerful packages like dplyr and data.table. We’ll explore each approach in detail, providing code examples and explanations along the way.
Click through for several examples.
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