Episodi
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This is a strange time for many technology professionals and their employment. It seems many organizations have open positions and are struggling to fill those slots with qualified candidates (one look at this). At the same time, many other organizations have followed the large technology firms (FAANG, MSFT) and laid off large numbers of their staff in the last year.
At the same time, with the hype and rapid growth of GenAI systems, we have companies that are looking to machines to fill some of their labor needs. Salesforce noted that they did not expect to hire more software engineers in 2025 as their plan was to use AI tech to help them write enough code. They've seen productivity gains with AI tech, so they aren't adding more developers. They still need human developers, just not more of them.
Read the rest of The Job Outlook for Database Professionals
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Recently there was some online complaints about social security numbers (SSNs) in the US being duplicated and re-used by individuals. This is really political gamesmanship, so ignore the political part. Just know that social security numbers appear to be one of the contenders used in many data models.
I found a good piece about how SSNs aren't unique, and have a mess of problems. Despite this, many people seem to want to use SSNs as a primary or alternate key in their database systems. They also aren't well secured in many systems, even though we should consider this sensitive PII data.
Read the rest of A Poor Data Model
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Episodi mancanti?
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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.
Read the rest of Your Biggest Data Model Complaints
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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?
Read the rest of Why Not Use AI?
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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.
Read the rest of Trust is a Funny Thing
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I don't know how many of you will be disappointed or impacted by this, but Azure Data Studio (ADS) is being retired, as of 6 Feb, 2024. It will be supported for a little over a year, until 28 Feb, 2026. On one hand I'm not surprised, and on the other, I'm a little shocked by this.
I have written a number of articles on ADS, and shown how things work, as well as pointed out a number of things that don't work well in the product or its extensions. These pieces have gotten a number of reads, and people have commented on them, so I wonder if there are a lot of you that are upset by this. Is this going to change the way you work? I will say that it will lightly change my work, as I do use ADS to connect to PostgreSQL, but not so much for SQL Server.
Read the rest of The End of Azure Data Studio
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I had never heard of data debt until I saw this article on the topic. In reading it, I couldn't help thinking that most everyone has data debt, it creates inefficiencies, and it's unlikely we'll get rid of it. And by the way, it's too late to get this under control. I somewhat dismissed the article when I saw this: "addressing data debt in its early stages is crucial to ensure that it does not become an overwhelming barrier to progress." I know it's a barrier, as I assume most of you also know, but it's also not stopping us. We keep building more apps, databases, and systems, and accruing more data debt. Somehow, most organizations keep running.
The description of debt might help here. How many of you have inconsistent data standards, where you might define a data element differently in different databases? Maybe you have duplicated data that is slow to update (think ETL/warehouses), maybe you have different ways of tracking a completed sale in different systems. Maybe you even store dates in different formats (int, string, or something weirder). How many of you lack some documentation on what the columns in your databases mean? Maybe I should ask the reverse, where the few of you who have complete data dictionaries can raise your hands.
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If your job as a developer or DBA has been like mine, it's a constant stream of requests to change something, often without enough information and short deadlines that create a bit of stress. There's always more work to be done, and while it might be a great job, you're often trying to finish something quickly enough to get to the next thing.
In this mode, how often do you think about creating (or modifying) the thing you're working on for today vs maintaining it for tomorrow. In other words, do you consider how easily your work can be understood, is documented, is designed to allow for flexibility, and can be enhanced without many (any?) side effects, or anything else.
Read the rest of Creating vs. Maintaining
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The short answer is of course, most of us can learn and improve our skills to become better developers, engineers, DBAs, etc. While we might not be able to become the 10x engineer that many aspire to be, we can certainly become a better employee inside of an organization.
There's a piece on becoming a more effective engineer, which is actually titled know how your org works. It a piece from an engineer that started with a tweet: The text was:You can either complain and pontificate on Twitter on how the tech industry *should* ideally work, or you can learn how your org *really* works and what’s rewarded, and optimize for that. Or quit and find another job. This might sound cynical - but it’s what it is.
That sounds a little harsh, but the reality of how your org works or is structured or interacts is a reality. We all have hindsight to look back and wish someone (including us) had written code better. We might be sure if we could change one thing, or add/remove someone else, or make some other change, then things would be better. We might feel that there is a simple solution. Those things might be true, but they aren't the reality of the situation.
Read the rest of Can You Become a More Productive Engineer?
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There are many, many choices for cloud database services these days. I would hope everyone is aware of the various IaaS options in public clouds with EC2, Azure VMs, GCP Compute Engine, and others. These are often the easiest way to move your workload, but you've really just moved a VM from one place to another (likely more expensive) place.
For managed databases, there are lots of choices, but you might not be aware of your options. I ran across an article that discusses the various flavors of managed databases in the big three public clouds for SQL Server. In the piece, there is a section that talks about when a managed database makes sense. I like that it discloses the development on a managed service is expensive.
Read the rest of The Managed Cloud Database Options
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