Voice of the DBA

Tag: Database Weekly

  • Has AI Changed Software Development?

    I saw a piece that asked the question about AI and software development, specifically ChatGPT, a year after its release. Has software development changed? It’s a question I’ve been trying to ask for myself, though I do think the way AI works for lots of code is fundamentally different than how it works for databases. Databases need a lot of context, with schema and relationships, whereas a lot of other code can be structured in a more narrow sense, focused on an algorithm rather than specifically needing to reference other objects.

    That’s not to say that a generative AI can write application code better than database code. I think in both cases it can be helpful or hurtful. As I read the article, I find myself agreeing that AI has changed software development. It’s a tool, and it can be useful. It can help structure code, point out issues, and help with building tests.

    That being said, I also agree with this sentence in the article: “…given that to write anything resembling maintainable code with AI, you’ll need some level of expertise in programming.” Everything I’ve seen from AIs still requires a review from a human that understands if the AI is on the right track in approaching the problem. I’ve written this a few times (and discussed it with others) that I think an AI produces junior level code in many cases, and it takes a subject matter expert to decide if that’s OK for the situation.

    However, I feel that AI does a few things really well. First, it’s a great search engine, able to understand multiple prompts in a row that narrow in the thing I might spend much more time searching for. It also does some nice predictive things in guessing what code is needed next. In most application languages, this is helpful. In SQL, not so much, since the SQL language lays code out in a way that makes it harder to predict things. The LINQ structure of from, where, select is much more cleaner in many ways. If only RDBMSes natively executed LINQ…

    If you’ve tried AI, what has worked, what prompts give you help? Is there anything especially time-saving you’ve found? I, and many others, are looking to understand where it can help us.

    Steve Jones

  • No Degree Needed

    For most of my career, I’ve seen many companies that hire white-collar workers, including their IT staff, require a college degree or the equivalent experience in the military. Often this has been something the Human Resources department has made a requirement in their job descriptions and requests to recruiters. This was a filter that stopped many talented people from even getting an interview.

    That hasn’t stopped a lot of people from pursuing careers as developers or IT staffers, and I’ve had many friends who have had successful careers without a degree.

    The world has been changing, especially since the pandemic, and many companies are no longer requiring any sort of university degree for candidates. There are still a lot of job descriptions that “prefer” a degree, but even that is changing rapidly. I hope at some point that we stop looking at degrees as anything other than a bit of experience in working through a project and not as any sort of qualification for a particular job.

    This week there was an article about seven ways to become a software engineer without a degree. The ways are: learn to program, earn a cert, contribute to an OSS codebase, write documentation, find employers who don’t care, be a freelance developer, and go to a bootcamp. Of these, a few seem redundant learning to code is probably needed to contribute to OSS or freelancing.

    Of these, I overall like the advice. Being self-motivated or driven is a skill that many employers appreciate. Showing that you are producing something useful in the world is a good way to create opportunities. It’s also a sign that you’ll work to be productive and not expect to avoid work after getting hired. I know I prefer people who go figure things out rather than those who wait for someone else to tell them what to do. I don’t recommend bootcamps, however, unless you are very motivated to take whatever you learn and then expand on it with OSS contributions or other tasks that showcase and expand knowledge.

    Finding a job is challenging at times, and certainly impressing someone enough to hire you is a task. A degree can help, especially with those who might be prejudiced towards university experience, but more and more people recognize that college doesn’t necessarily prepare you to be productive or a great employee. You can prove that to people yourself with some work, some documenting your efforts, and some good soft skills to explain what you know.

    Steve Jones

  • Using AI with Data Tasks

    The hot new technology of the year is AI. Between ChatGPT, Copilot, and generative AI, it seems that this is invading the world of computing at an incredible rate. Whether this becomes really useful and valuable or not is something that we will seem over time. There have been plenty of trends in this area in the past that haven’t become as ubiquitous as the hype would lead you to believe.

    I’ve done some light experiments with AI on my blog. To date, I haven’t found this to be that useful, other than a few cases where I basically used an AI to search the web for me. Rather than read a bunch of SSC or Stack Overflow results, the AI summarized things.

    Somewhat.

    I definitely had to test and verify the code more than I feel I’ve done with code posted in a forum. Of course, I do less experimenting because the AI results were a little more targeted to what I needed, rather than my cobbling knowledge and partial solutions together. I’m also not sure which I prefer.

    I would like to use AI for data work, and there is an article that talks about some of the ways that we’ve used AI in the past. Data profiling has made sense, and I can see value here. For data security, I’m not sure how helpful AIs have been. I’ve looked at some products, and I don’t know that I think any of them do a great job of identifying data. They do make it easy for whoever is assigned the task by doing some of the work, but they aren’t a panacea. They make mistakes, just like humans do.

    I do think data observation and looking for anomalies is a place where AI can really shine, but that’s not the data work that many of us do. It matters, but for most of us, this isn’t something we deal with.

    The future of AI was more interesting. The idea of data homogenization, taking data from different sources, and fitting it to a data model is interesting. Of course, the AI can’t make too many mistakes, or the time correcting might overwhelm the time saved. I think we see that now with humans who we ask to ETL data. If they aren’t good at it, or make lots of mistakes, those of us overseeing them might just do the entire job ourselves.

    I know that AIs are still new and immature, and while there is a lot of potential, they feel like junior staffers now, needing more handholding and micromanaging than I like to do. Perhaps they will change our careers and the way we work, but I don’t know how quickly, or even how deeply. Already I find lots of companies putting restrictions on what their employees can do with AI, which makes me think this might be more a targeted, niche technology more than a general, use-it-everywhere solution.

    Steve Jones

  • The Choice of SQL Server Version

    Every quarter Brent Ozar publishes some data from his SQL ConstantCare® service. This is a service where companies contract with Brent to install a service on their instance, collect data, and give them simple, short daily emails on things they should check. It’s a good service for companies who don’t employ skilled DBAs and may relay on a developer or sysadmin to manage a SQL Server instance. While this is a self-selecting group of organizations, across his 3,100+ monitored servers, there are likely trends that could apply to the world of SQL Servers in general. After all, for every gung-ho, let’s-upgrade DBA, there’s probably a sysadmin with a similar mindset.

    In any case, the summer 2023 report form Brent shows that SQL Server 2022 adoption has slowed. His report is down, though I doubt anyone downgraded. Perhaps someone was testing and added a 2022 server in the spring they removed. Or maybe they tried 2022 and then went to the cloud. He does show 2019 growing and 2016 shrinking, which dovetails with what I see from my memory of various questions at SQL Server Central. I see people asking about moving from older versions to 2019 much more than 2022.

    I wonder what that is? Brent thinks this is because people standardized on 2019 installs and haven’t moved to 2022. So anyone adding new instances likely uses an image/setup/process for 2019. That matches with a few of my customers, who haven’t had some of their install or security processes updated and are still adding 2019 instances. I think that’s short-sighted as 2019 is 4 years old, but I also understand that people get busy and updating anything for a new version isn’t a priority.

    There have also been some problems with updates, and Brent thinks companies are skipping 2022. I don’t know, but I do wonder what you think about your estate and how things are changing. I assume if you are still running 2014- at this point, you’ll just live with the server as long as you can. I hope you’re at least on a VM so you can restore quickly if there are issues (assuming you back up VMs).

    If you run 2016/2017, are you looking to upgrade? Considering 2022 or stick with 2019? Or kick the can and hope that SQL Server 2024 or 2025 will be better? Actually, take a guess as well on the next release date. I’ll take a page from Brent and run a contest for you to guess the next release date.

    Steve Jones