Voice of the DBA

Author: way0utwest

  • Back at Small Data SF in 2025

    Today I’m in San Francisco at Small Data SF 2025. I went to the conference last year and thought it was a great event. Watching people talk about data and how we might look at managing smaller systems, at dealing with the challenges of exploding volumes by querying, storing, and handling less data was fascinating. The event had me me really thinking about ways in which we can build better performing (and cheaper) systems.

    To be clear, small data isn’t very little data. Often this is still 100s of GB, perhaps low TBs, but it’s getting away from the idea of thinking we’ll be working on PB-sized big data systems, or that we even need to.

    Last year there were lots of talks on data analysis, querying, and even AI, but using smaller sets of data in practical ways that provide value to organizations and individuals by judiciously choosing data sets. Either recent or representative data.

    This helped me think of new ways for subsetting, which is something I’ve been pushing at Redgate for our TDM product.

    I’m looking forward to the talks. This is a quick trip. I skipped the workshops yesterday since they weren’t that great last year (too many product/company pitches from Silicon Valley) and flew out last night after coaching kids in their first practice. At the conference today listening to talks and doing networking get together after before flying back early tomorrow.

    A quick trip, but I’m sure I’ll lots to write about (and think about) in the future.

  • Republish: Practice Until You Don’t Get It Wrong

    I was in the UK last week and since I was gone for a week, I’ve decided to take a day off with my wife.

    You get to read Practice Until You Don’t Get It Wrong, which is something I believe in. Or listen to the podcast: https://traffic.libsyn.com/voiceofthedba/PracticeUntilNotWrong_92_v2915.mp3

     

  • The Selfish Case for Learning AI

    I ran across this article on a survey about AI usage recently. The headline is this: 55% of businesses admit wrong decisions in making employees redundant when bringing AI into the workforce.

    That sounds a little ominous for those making these decisions, and a lot of you might be saying, “I could have told you that. Using AI to replace people is a bad decision.” On the surface, I agree. I dislike the idea that companies will opt for a semi-competent AI bot or agent to replace people, thereby further exacerbating the challenges faced by many workers in the modern world.

    However. 55% means 45% didn’t feel that way. That’s almost a coin flip for executives who want to make a decision about whether to terminate some employees and replace them with GenAI tools, especially workers who might do things like customer service or tasks that are narrower in scope and “seem” like good fits for an LLM.

    A lot of the stats in the piece are presented in a way to paint AI as risky, but the numbers are often less than 50%. To me, I worry that this is a bet executives might make. Especially when this might result in a bigger bonus or dividend for them personally. I never discount the selfish nature of executive decisions.

    So, what is my selfish case for learning AI if I might get replaced? The big number is this one: “…80% of business leaders plan to reskill employees to use AI effectively…” For me, in my job, I want to be one of the people execs see as effectively using AI.

    I need to spend time learning how to, and how not to, use AI tools. They can be helpful, but they can also cause problems. I need to examine where they help, how much time they save, and when to abandon them and just handle a task myself. That last skill might be the most important. I also need to ensure I learn to work efficiently with the tools to save time and become more effective. That takes some effort and focus to learn to use the tools well.

    There are always going to be executives who will make the decision to let someone go. Your (selfish) job is to ensure that you aren’t the one chosen.

    Steve Jones

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

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

  • A New Word: Foilsick

    foilsick – adj. feeling ashamed after revealing a little too much of yourself to someone – allowing them too clear a view of your pettiness, your anger, your cowardice, your childlike vulnerability – wishing you could somewhat take back the moment, bolting the door after a storm had already blown it off its hinges.

    What a visual. The door blown off its hinges from a storm, and you desperately trying to set it back into the opening.

    Blurting out something in an emotional moment is likely something many people have done. I would guess parents as much as teenagers feel foilsick after an argument or a moment of passion in which they say something they didn’t mean.

    In the modern world, we might do that with messages or emails as well. I find myself trying to avoid putting myself into the place where I might feel foilsick and I often take a moment to draft something in Joplin (my notetaking app) before I put it into Slack or email. I can’t accidentally send it and then feel some regret over what I said.

    I think the avoidance of ever feeling foilsick often leads many of us to not say something we feel, or admit a challenge, precisely so that we aren’t vulnerable and regret our words. As I grow older, I realize that being vulnerable isn’t going to create a foilsick feeling in many cases. It’s going to bring me closer to someone else, or help them help me.

    From the Dictionary of Obscure Sorrows