Voice of the DBA

Category: Editorial

  • Your Value from a Conference

    The PASS Data Community Summit 2025 was held in Seattle last month, and it was an interesting event for me. I wrote a wrap-up on my blog, but a few things stood out. The event was a little smaller, with over 50% first-time attendees, but seemed to be a bit more vibrant. Perhaps people coming for the first time added something that I hadn’t expected. I was a bit over-committed, so I didn’t spend a lot of time in the public spaces, but things felt a little different the few times I was in the expo hall or the hallway track.

    I ran across a Reddit thread on the value of conferences, and it got me thinking. What is the value that you get from attending a conference (or an event). If your employer pays you might feel that you should bring some value back to them when you return. That’s the premise of the thread, and I know there are plenty of people that feel that way. However.

    Should you value your time and effort any less?

    What if you attend a SQL Saturday or other local event for free? Shouldn’t there be some ROI for you? With that in mind, I’m asking the question of you: what value do you get from attending a conference? For any type, size, shape, topic, etc. conference, let us know what you do go, or would go, or maybe would choose to skip the opportunity.

    I’ve attended lots of different events in my career. My perspective varies depending on the event. I’ve attended customer conferences for a vendor, where I want to learn what might be changing, how others use the products, ask if there are solutions to our challenges, or even get the chance to influence the product development people. For local events, it’s networking and the chance to see a session on something I am interested in learning more about or a topic that might be of use in my job. For large industry events, there’s a larger scale, and more choices of topics, so I might get the chance to explore something I know little about or see some great speakers inspire me.

    However, I get out what I put into it. If I am passive and just sitting there hoping I learn something from a talk, I’m can be disappointed. That’s an expensive way to learn something. The real value comes when I ask questions of the speaker afterward (or listen to others’ questions). I learn more by discussing the talk with other attendees, or having random conversations about the things others are doing/learning/trying/etc. in the hallways. Engaging others gives me ideas and inspiration I don’t get from a lecture.

    The other thing that comes from a conference is a break from work. I try hard not to schedule work things or respond to messages while in sessions. I want to unwind, let my brain change gears, and hopefully get recharged in a different atmosphere. There’s also the chance to visit another city and perhaps see a sight or two. I love Las Vegas for this reason, taking my wife and seeing a show after networking and learning all day. It’s a great break from work.

    I think there are good reasons to send people to conferences: learning, getting inspired, recharging, or even as a perk for employees who are working hard the rest of the year.

    Steve Jones

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

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

  • The Challenge of AI

    In his book, The Coming Wave, the CEO of Microsoft AI laid out the risks of AI tech bluntly. “These tools will only temporarily augment human intelligence. They will make us smarter and more efficient for a time, and will unlock enormous amounts of economic growth, but they are fundamentally labor-replacing,” he wrote. Suleyman advocated for regulatory oversight and other government interventions, such as new taxes on autonomous systems and a universal basic income to prevent a socioeconomic collapse. This book was published before Suleyman joined Microsoft.

    Satya Nadella is more optimistic than his new deputy. In an interview at Microsoft headquarters, while sitting next to his human chief of staff, Nadella said that his Copilot assistants wouldn’t replace his human assistant. As his chief of staff sat typing notes of the conversation on her tablet, Nadella acknowledged that AI will cause “hard displacement and changes in labor pools,” including for Microsoft. Judson Althoff, Chief Commercial Officer, said that Nadella was pressuring his team to find ways to use AI to increase revenue without adding headcount.

    In 2025, Microsoft has reduced quite a bit of its workforce. Over 9,000 earlier this year, though perhaps there will be some hiring in the future, according to Nadella. Nadella contends that AI could end up delivering more societal benefits than the Industrial Revolution did. “When you create abundance,” Nadella said, “then the question is what one does with that abundance to create more surplus.”

    As I discuss AI with different people, I get wildly different opinions. The pace of GenAI model growth across the last two years has led quite a few people to believe that the technology will approach mimicking the average human’s intelligence in just a few years. That’s a scary thought, and it certainly could lead a lot of executives to place a bet on fewer human employees and more digital ones.

    However, many more people believe that the GenAI models still need a lot of guidance, and they are best suited for partnerships with humans. That’s good, in a sense. If a smart or talented human can use an AI partner and get a lot done, that means we still need some humans.

    Some.

    That use of AI by a few talented people might also lead us to a reduction in labor for a lot of organizations. Maybe fewer humans get more done with AI, and it’s possible organizations want to make that trade. It’s easy to think we’ll find things for more humans to do, but computers are incredible levers, and this worries me.

    A little.

    What I also think is that there is so much work we’d like to get done, but we can’t, at least in the technology space. We don’t have enough people to do the work, so GenAI agents or partners working with humans might let us catch up on the backlogs we have.

    Of course, I don’t know that all that backlogged software we went is something we need, if it’s good for the world, and if it will end up putting even more people in the real world out of work.

    Lots of challenges ahead. Let me know what you think.

    Steve Jones

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

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

  • Growing Artificial Intelligence

    This editorial was originally published on Jul 4, 2016. With Steve on holiday, this is an interesting look back almost a decade into the past at AI technology.

    There’s a fascinating piece over at O’Reilly that looks at what we might consider Artificial Intelligence (AI) to be. The discussion looks at Deep Blue, Watson, and AlphaGo, all of which have defeated humans in game competitions where we might expect some intelligence is needed. We could argue that, but certainly, these computing machines have done more to display knowledge than the best humans at certain endeavors.

    What is interesting is that each of these machines, while very competent in its area, is specialized. AlphaGo can’t play chess, nor can DeepBlue play Go. Each has been tuned to a specialized area, and also trained to excel in that area. This isn’t fundamentally different than humans that train and specialize themselves, though certainly we find humans have more capabilities in a general sense (for now) than machines.

    As we look to grow intelligence, however, there is one thing that’s commonly needed in both artificial or machine intelligence and human intelligence: data. Whether a human is training themselves to solve a particular problem, compete in a game, or even excel in a sport, they need lots of data. We gather this with our senses as well as by examining what others have one, contemplating actions, trying out different actions, ideas, or concepts, and then adjusting to improve.

    This is what researchers are also trying to do with gaming machines, with self-driving cars, and even with bots. That last item is interesting to me, as I haven’t paid much attention to bots. A long conversation with another SQL professional got me interested in, and intrigued by, the idea of software robots that might handle various complex tasks better than the FAQ method that so many applications and websites use. I wasn’t sure these would be useful, but I have found the Slackbot to be more helpful than the help or searches for some tasks.

    There’s work to be done, and I know the Slackbot (and other machine intelligence software) needs to be trained better. This requires data. Lots of data, and possibly lots of hand holding from a human. For many areas, such as relatively low-level customer support or problem solving, I wonder if a bot could be trained to work better than the simple decision tree algorithms like those found in the Windows Troubleshooter.

    There are various ways we might grow this software to help us, and make no mistake, we will need to grow it. Plenty of businesses are becoming excited about machine learning, the R language or Python, software bots, and more. In all the cases of implementing these systems, the one demand that will impact many of us is the need for lots of data. Data that’s organized, that is relevant, that we can use to separate out successes from failures, and evaluate our particular problem better. We will need to group data into knowledge and then feed it into software.

    I think this is a bit different than how most of us have used data over the years. We’ve often collected, manipulated, aggregated, summarized, and spit data back out to (ultimately) some human that can make a decision. Most of us haven’t worked with sending data to a machine intelligence and somehow then helping it to understand how to respond on make a decision.

    My suspicion is there will be lots of work for us in the next decade in helping machines to use data and understand it, maybe even to use them to help us gather, organize, clean, and manipulate data better ourselves. It’s an exciting time to be a data professional, and I’m sure some of you will work on a few very exciting projects in the future.

    Steve Jones

  • Refactoring SQL Code

    One of the things I see software developers often talking about is how they refactor code. As they touch a class, method, etc., they may take the time to refactor the code to make it cleaner, perform better, or just add some documentation. It seems that a regular part of a software developer’s job is refactoring code in the codebase.

    That is unless they see a “don’t touch this, no idea how it works” comment. There are plenty of those, and often everyone leaves that code alone.

    I was thinking about this when I saw this article on strategies to refactor sql code. The article seems written more for PostgreSQL, but there are items that relate to T-SQL as well. The main thrust of the article is about trying to rewrite code to DRY (don’t repeat yourself). The more changes you can make to shrink code, either to make it easier to read or avoid repeating those copy/paste items, the better off your team will be. It’s easy to think those copies aren’t a big deal, but it’s easy to update code in one place because that solves the problem you were given, and forget to fix all the copies.

    I don’t know that anyone should implement all the techniques listed, but they are things to think about. Using CTEs, Views, APPLY, the WINDOW clause, and more can help improve the health of your codebase and make it easier for all the members of your team to understand how the system works.

    I wonder how many of you have a refactor mentality when you touch code, or do you tend to leave things alone and add new queries/objects/etc. to your database. I wonder if the fear of breaking something that might be used by other code is on your mind. Or maybe you suffer from “not invented here” (NIH) and just add your own code.

    If you refactor code, then what things do you look to change or improve? Any tips/tricks/guidelines you’d share with others? If you don’t refactor code, why not?

    I think testing is a big part of refactoring. If you have tests, then you can be less worried about your changes breaking something. There is a great video on practical refactoring. It’s from the software engineering view, and it’s long, but it’s worth a watch if you have a few moments.

    I wish more people tested their SQL code and refactored poorly written (or poorly performing) code on a regular basis.

    Steve Jones

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

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