Author: way0utwest

  • Updating the Data API Builder

    I was updating my session for the Data API Builder (DAB) recently, mostly to work with the MCP server capabilities. As I was trying to get this working, I realized that the MCP capabilities were newer than my DAB version. I had v1.4

    2026-06_0232

    Wow, that’s old. The Overview page for the SQL Server MCP site says v1.7 is needed and 2.0+ has bug fixes. I need an update.

    I had this in my slide deck, but the dotnet tool is used to update the DAB. The command is

    dotnet tool update –-global Microsoft.DataApiBuilder

    This showed a download and then in a few minutes it was done. I could see I had an updated version.

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    And an MCP server!

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    A Further Update

    I checked a few weeks later and couldn’t remember the command, but I decided to try the install command. That worked as well, and I got an even newer, 2.0.12, version.

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    Still no timestamps from the logs, but I’m every hopeful.

  • Preserving Data

    Most data professionals I know go out of their way to take care of the data entrusted to them. Most people ensure backups are running, lots (hopefully most) test their restores. A few will ensure a good rotation their data offsite. Some of you might have formal rotation schemes, and some might just keep a rolling list of xx backups available.

    Likely a few of you don’t worry about anything other than the last full backup, which is a risker approach than I’d take.

    In the past, I’ve often kept around monthly backups for a year, usually with more granular backups inside of the month. Beyond that, depending on the system, we might keep quarterly backups or yearly ones for a longer period. These days with cheap storage and automated solutions, I’m sure many of you just assume your backup system keeps xx backups around. the cloud providers will keep point in time backups if you use Azure SQL DB (7 days by default) or AWS RDS (1 or 7 days, depending on the provisioning method). If you use VMs or other systems, you ought to be aware of how long backups will be kept and ensure that fits inside your RPO.

    This came to mind as PBS, a US broadcaster, almost lost most of their archived data recently. Their provider stopped responding to them and they couldn’t get to the data, which was stored in Iron Mountain data centers. They sued and got access to ensure they could access and use this data. A win for them, and really, for many of us.

    I don’t expect Azure or AWS to go under, but some of you are using third-parties for backups, even in the cloud. If your provider goes under, can you access your data? I can guarantee if any of these companies has issues (financial, hacking, ransomware, etc.), there will be a few clients that need a restore that day. Resolving this in the courts is likely to be successful, but after how many days?

    Backups are important, but only when they facilitate a restore. It’s easy to get complacent and think because you’ve been running backups that you’re protected. Test that restores work. Have a plan, and maybe a contractual clause, that ensures you can get to backups in the event of issues. This won’t protect you from everything, but it can help speed things up.

    And if you’re like me, keep at least the last backup (or two) local to your system, in a place that you can get to quickly and easily. It’s fine to assume the automated PIT backups will be there, but if AWS or Azure has issues on the day I need a restore, I’d like to think it’s worth a small cost to me employer to ensure there’s at least one backup separate from the automated service. That SLA refund isn’t likely going to cover the lost business when your database is down.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.

  • A Daily Report from Claude

    Redgate had some Claude training recently, which I went through as my knowledge has been gained in bits and pieces and is fragmented. I wasn’t sure I’d get a lot out of it, but I was surprised by a few things I learned.

    One of these was scheduling a task to give me a daily report. This post looks at that process for me. I’ll walk through what happened, and then a summary below of what I think of this.

    This is part of a series of experiments with AI systems.

    Getting Started with Skills

    One of the first demos shown was to build a daily snapshot of what things need to be looked at and handled. The default in Claude is the /morning command. I ran this, looking to customize it, and Claude decided to create a new skill for me, based on this, which it named “morning-plus”.

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    I had previously added the Microsoft 365 Connector, so the skill could read my email. That’s good, as this is a read-only view for me, and it’s local to my machine. I’m sure there is some security risk, but this is managed and limited by Redgate, so I’m assuming this is good enough for my work.

    The next thing was to alter the view. I had a weird graph of lines that seemed to try and show the height of a graph implying the length of a meeting or a business of the day, but that’s not helpful. I decided to ask for a calendar list.

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    This gave me a nice look at my day, which is shown below:

    2026-08_0269

    Another thing I wanted to do is keep an ongoing TODO list as I have various things that aren’t in my calendar. A bunch of these things are repeating or ongoing, but having a list helps me stay organized. I might need a way to order them, but for now I asked Claude to add this. It guided me to using a folder to store this, which is what I wanted.

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    I also decided to keep the report here, as this helps me stay organized. I can keep the todo.md open in VSCode or elsewhere and edit as needed (or ask Claude). I like to do some editing myself, rather than waste tokens. If I have to type in a prompt, but not just edit the doc.

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    In the past I’d have tried to figure out how to schedule things. Here I just asked Claude. It did the work for me.

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    Once done, I have an item entered in my Scheduled area. This is a Claude thing, so Claude needs to run, which is fine. My desktop is running all the time.

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    I clicked the item and selected Run Now from the menu that popped up. This ran and went through all the tasks and produced a report. It took a few minutes, maybe 5? It’s slow, but not a lot of stuff going on when this will run for me, so it’s not a big deal. The report:

    2026-08_0278

    Not bad, but I also want to get anything from overnight that is important. I tend to look at Slack for mentions/links, so I added the Slack connector, which Redgate has authorized. This will let the agent scan for things that mention me and I can get a summary rather than searching through all folders.

    I added a prompt to help here, which is great.

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    That didn’t work, and Claude explained why.

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    Sad smile

    One note, each time I altered the skill, I had to approve the changes after Claude decided what to do. It’s a good idea, but the list of stuff it lists in a stream of text is too much to read, so I’m not sure how well this secures things.

    I also have to re-approve a changed skill to access my e:xxx folder on each run. I guess it’s good, but in a practical sense, I’m going to just approve this.

    The last thing I added was a Windows Scheduled task to run Edge and load this page. This was easy to do, and it will bring up a browser on my desktop that I can see when I log in. Now I can skip some of the checks I might do early in the am, knowing that I’ll get a view of my day when I get to my desk.

    Summary

    One of the interesting things the trainer noted was that when you start using a new tool, productivity can go down until you get the hang of it. This applies to many tools, but certainly Claude and AI chat/agents. It takes some time to see benefits, which is something I’ve noticed myself. Part of this is learning to use the tool, and part is deciding how you want to use the tool.

    In my case, I was skeptical this was actually a useful thing. My days can be chaotic and crazy. However, I’m willing to give it a try. I am starting to have more and more things that I need to keep an eye on, and things that span more than a day. I use calendar reminders constantly, but there are a lot of moving parts here. Keeping a todo list is a start, though I likely need to add some dates or priorities. I’ll play with this over time.

    The lack of Slack integration is annoying, but if I can keep other things organized, this will be helpful.

    Is this helpful and worth it? I don’t know. This is an experiment on my part, which I’ll run for 3-4 weeks to see if this is helpful in tracking lots of disparate work. I certainly forget some things and then end up working late, or miss deadlines.

    Is this worth the cost? Running a report costs $0.82 in its current iteration. Is it worth $1 to organize my day and prevent missed items? Perhaps. I’m not sure, but this is an experiment.

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    A small AI thing, but at $200 a year, this might be a nice productivity helper for me, partially to ensure work is done, and partially to reduce stress from the chaos of my life.

  • Collecting Data is Hard

    Data is the lifeblood of much of the world today. Not necessarily big data, and certainly not perfect data, and definitely not just digital data. Organizations, individuals, governments, really everyone out there are making decisions based on data. You might think it’s going to rain, so you cut the grass today, or maybe defer adding fertilizer. Your organization sees demand for a product increase, so it orders more and produces more. Government is always using data to make decisions about resource allocation. We might not think governments make great decisions, but they do use data and data matters.

    Recently I was reading a science fiction book (I, Starship) about the future, where a person’s brain (Henry) becomes uploaded to manage a starship. This ship will travel light years away for 80 years and they need the human crew asleep in hibernation to survive the journey. The interesting thing, to me, was a part in the book where there is a discussion of why Henry was uploaded and why AIs aren’t advanced enough to run the starship. There’s this quote: “The first generations (of LLMs) performed well, but as time went on, we entered a situation where more and more of the data available to train them on was itself machine-generated. So, instead of mimicking high-quality human output, the outputs got more garbled.”

    I worry about this as the current models are sucking up so much data to learn, but so little of the new data is being generated by humans. We already see plenty of AI-slop on the Internet, with fewer and fewer articles, blogs, etc. being human generated. I’m sad because people don’t share as much of their own thoughts, knowledge, etc. This is especially true in light of the AI companies taking individuals’ work for training without compensation. Indeed, I worry that many places will go the route of Stack Overflow, where they essentially fail.

    I’m worried about that here at SQL Server Central, as I see less questions being asked by humans and less discussion about the nuances of database challenges.

    However, there are AIs out there also polluting the world. This was a piece from last year that more AIs are taking surveys and polls. Reddit is seeing questions being asked, and I’m sure there are AIs answering them. How long before the amount of AI generated traffic dwarfs human generated traffic? I mean new data, not consumption. I expect plenty of humans are going the way of the people in WALL-E and just consuming data. They’ll continue to watch untold numbers of reels, shorts, Tik-Toks, etc.

    Are we going to see less “real” data and more generated data? I already have seen no shortage of issues from customers trying to use synthetic data for testing. It doesn’t match the real world well, but if they stop getting real data from customers and more from other bots, maybe it won’t matter. Of course, I’m not sure how well their systems will perform in the real world.

    GIGO is a real issue, and I expect a lot of companies will learn this as the volume of AI-generated data increases.

    Steve Jones

    Listen to the podcast at Libsyn, Spotify, or iTunes.

    Note, podcasts are only available for a limited time online.