Voice of the DBA

Category: Editorial

  • Your Biggest Data Model Complaints

    I’ve been working with databases for a long time and there are no shortage of things I’ve seen other people do that I don’t like. Sometimes I shake my head a little. Sometimes I might groan inwardly (hopefully not aloud), and sometimes I might make an effort to convince someone else to do something differently.

    Sometimes I’m really annoyed (or angry) and don’t even know what to do.

    I know that most people are trying to just get work done. They might rush through something and not do a good job, perhaps because of oversight, or perhaps they are naïve about the effects of their work. Maybe they have ingrained habits and are unwilling to change. Maybe there’s another reason (let me know if there is one).

    However, no matter the reason, it can be very frustrating to work on poor database designs. There might be other things that bother you, but today I’m focused on the data model. Do you see poor naming of objects? Are there problems with the way they structure their entities? A lack of indexes?

    What are your biggest complaints about the structures in your databases?

    While I am looking forward to your stories, I want you to be professional. We’ve all made mistakes, and there is likely some (most?) code we’ve written that we wish we could redo. Don’t embarrass anyone or any organization, but let us know which types of problems or anti-patterns are your biggest complaints. Bonus points if you can do it in a humorous story.

    Steve Jones

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

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  • Why Not Use AI?

    Erin Stellato, a program manager at Microsoft, asked a very interesting question on LinkedIn: “why do you *not* want a Copilot in SSMS?”

    That got me to stop and think a minute. Why don’t we want to use an AI to help us? It’s a good question, given the hype and (maybe) potential of the technology. While it might not help you now, or with your specific thing, it might help others, so are there good reasons not to use AI technologies, like the GenAI LLMs?

    Let me know today. What are you reasons for not using them (apart from cost or restrictions at work)?

    I will say that I rarely use AI tech to get work done, or even in my home life. I just don’t enough places where I think I need help outside of a search. I search a lot, but I haven’t found AI to be faster than searching. Sometimes it is, but sometimes not and the unreliability of the tech bothers me. That being said, I do have a tag where I write about the AI things with which I am experimenting.

    I think for many of us, AI is too amorphous and unclear. We don’t quite know when it helps or doesn’t. We don’t know how to judge the quality of it. It’s also not a habit or integrated into life. Most of the suggestions I see in various places aren’t things I’d ask. The default page in my local mode has these suggestions:

    • tell me a fun fact
    • show me a code snippet of a website header
    • give me ideas for what to do with kids’ art
    • help me study for a college entrance exam

    That last one might be the only question I ask, not for college, but maybe for something like an MS exam. However, is the AI better than a search? Maybe, but I’d have to try it. Right now I’d be tempted to just search for a list of things to study. Maybe the AI helps me find those better, but really I’d want it to quiz me on different things.

    The problem is I don’t trust it to ask good, relevant questions, or necessarily give me the right answers if I asked it to quiz me.

    I guess ultimately is I don’t have enough “I think an AI is better” reasons over the do what I normally do. Without substantial evidence AI is better, I don’t use it much. Do you feel the same way?

    Steve Jones

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

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

  • Trust is a Funny Thing

    I caught an article on AI skepticism and there was a point in the article where trust was mentioned. Specifically the reasons that people distrust an AI or tech tool is that it makes a mistake, so they stop using it. A few examples of this were using a writing AI that made a grammar mistake or a GPS routing device that added a wrong detour. In those cases the humans stopped using the assistance of the algorithm because they felt it wasn’t trustworthy.

    What’s fascinating to me is that I had this same conversation with a human the day before. Someone mentioned they were working with a group and they misstated something. After that, the group stopped listening to all this person’s advice, thinking it was all suspect. Essentially one mistake overrides everything else.

    Trust is a funny thing. It takes time to earn and gain trust from others, and it can be lost quickly with an action. Trust is a reliance, a belief, a confidence in something or someone. The way the GenAI is framed, and the way a system is presented to a user can have a huge impact on the level of trust we give to an GenAI-system. Tell someone the system is trusted or others are using it raises trust. Tell someone to be wary, and they’ll trust the system less.

    I find that GenAIs are unreliable but not completely. They are trustworthy in some ways, but not in others. There are a few variations in the article (and in other places) that note that GenAIs are helpful, but we need to review their work. Essentially trust but verify, which isn’t a bad policy for any interaction with humans or AI systems. We learn to trust our co-workers, but that takes time. Some we might never trust and always review their work, while others we accept what they give us with minimal review.

    It’s interesting to see such a wide variety of responses to the usefulness of GenAI systems. Some people find them amazing, some find them useless, some use them daily for small things, some never bother to submit a prompt. I find myself cautiously using them more and more, especially my local models, trying out different prompts in different areas. One thing I got out of the article is I ought to have more conversations with the GenAI, much as I would with a co-worker. I’ll try to do that more in the future and see how it goes…

    In the meantime, how much do you trust AIs, other computer systems, or coworkers?

    Steve Jones

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

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

  • Moving On After a Technology Fail

    Recently my smartwatch broke. I was coaching volleyball and demonstrating something to a few kids when a ball hit the case of my watch just right and broke a corner there the watch band attaches. I’ve been playing and coaching with my watch in this way for many years and never had an issue, but apparently there was enough material fatigue that this time something snapped. I was very sad as this was my ten-year gift from Redgate, which I’ve loved, used, and cherished for 7 years now.

    I wonder if there’s a 20-year gift …

    In any case, I lived for a day before I realized I really depend on my smartwatch. I quickly realized that I constantly look at my watch to check the time, run a stopwatch at volleyball, track my heart rate and exercise for health, and most importantly, wake me up with a vibration in the morning. Before I had this I set an audible alarm, which my wife hated. At the time the case broke I was very busy, and after a quick set of searches and very minimal evaluation, I just bought a Garmin Venu 2Sq as a replacement. It was inexpensive, but appeared to do most of what I wanted. If I decided I didn’t like it, I wasn’t out a lot of money.

    I contacted Garmin, but they said they wouldn’t repair or replace cases. Maybe they assume technology that is more than 5 years old is too prone to failure and not worth fixing? Maybe they just want to sell new products and not support old ones? I get all that, but this age of disposable digital tech is a bit annoying and mildly upsetting to me. I constantly fix old things on the ranch and I like keeping devices going as long as possible. Why not make cases replaceable? I feel the same way about a few devices that have embedded and built in cords. One of my Google cameras had a cord failure when a cat chewed it and the entire device is not junk because I can’t repair this tiny cable and Google won’t. But I’m getting distracted here.

    This new watch is very different. Less buttons, more touch screen, and a different type of OS. I am having to learn how to use a new tool, which is both exciting and annoying. I am less productive in some ways as I learn a new tool, and I’m sure I’m missing things because I just want the tool to work rather than invest the time to learn about (potential) ways to use it. I know that there might be plenty of features I learn about that I’m uninterested in using, and I’ll have wasted time.

    I see this often in technology. Many of us get used to working with tools in a certain way, and we learn to be productive. We get comfortable, develop habits, and work around annoyances. If the tool changes, or we are forced to use a new one, often we don’t like the change. We may feel lost and not see the advantages of a new tool.

    I see this all the time as I work with customers. Sometimes I can see better ways they can accomplish tasks, and sometimes I see the cost of change is too high. Even a more efficient way of working can’t overcome a loss of productivity for a long period of time if too much change is required. Leaning on existing tools, skills, and habits can be efficient and comfortable. Going through the hassles of change can be worth the effort. Like most things in the database world, the devil is in the details and the answer to the value of changes is it depends. Sometimes a new tool is valuable and sometimes it is not worth the effort.

    Almost a month into a new watch, I’m unsure of whether I like it or not, but in the short term, I’m too busy to spend time looking for a new tool. Unfortunately, that’s the state of the world often for many of us. We live with good enough.

    Steve Jones

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

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