Tag: syndicated

  • T-SQL Tuesday #190–Mastering a New Technical Skill

    It’s time for T-SQL Tuesday again and this time Todd Kleinhans has a great invitation that is near and dear to my heart: mastering a new or existing technical skill. That’s been a lot of what I try to inspire people to do at SQL Server Central.

    Make a plan and start learning. And respond to Todd’s invitation and write down your plan and share it. Start a blog, use Linked In, whatever. Spread the word on socials as well.

    If you want to host, I’m always looking for hosts for T-SQL Tuesday. Ping me on Twitter/X, BlueSky, or LinkedIn.

    Mastering a New Tech Skill

    Like Todd, I’m interested in AI and I think it will dramatically change the world in the coming future. I also think it’s a bit of a technical skill that is important to learn. I wrote about this a bit in last month’s post.

    How do I work with a GenAI model and improve my technical skills? The easy answer is more and more. I’ve been having more conversations with Claude, usually looking for ways to help me solve a problem or write code, and then ask the GenAI to explain things.

    However, I wrote awhile ago about an experiment in helping someone else learn something: Can an AI Help Me Find a Job?. For me, I’ve been looking a bit more at DataBricks, as I hear this from clients all the time. I wanted to gain some skill here, so I decided to ask Claude to help me.

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    I got a good outline of things to do across a few months. I then asked for references and got some:

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    The next stage for me is to start embarking on this journey a few nights a week and learn some things that might help me both in my job, and potentially in a future position if I need one.

    My Complete Outline from Claude

    Here’s the end result, with links.

    Databricks Learning Outline with Resources

    Phase 1: Foundations (1-2 weeks)

    Understanding the Basics

    • What is Databricks and why it’s used
    • Core concepts: clusters, notebooks, workspaces, and Apache Spark
    • Databricks architecture and modern data stack integration

    Key Resources:

    Phase 2: Getting Started (2-3 weeks)

    Hands-on Basics

    • Navigating workspace interface
    • Creating and managing clusters
    • Working with notebooks
    • Basic data import methods

    Key Resources:

    Phase 3: Data Analysis Fundamentals (3-4 weeks)

    Core Analytics Skills

    • Data exploration and cleaning
    • Working with different data formats
    • Basic SQL and PySpark operations

    Key Resources:

    Phase 4: Intermediate Techniques (4-5 weeks)

    Advanced Analytics

    • Complex transformations and ETL
    • Streaming data and machine learning
    • Performance optimization

    Key Resources:

    Phase 5: Production and Best Practices (2-3 weeks)

    Professional Development

    • Job scheduling and workflows
    • Security and monitoring
    • Integration patterns

    Key Resources:

    Additional Learning Platforms:
    Certification Path:
    Community and Support:
    Getting Started Steps:
    1. Sign up for Databricks Free Edition: Visit the Databricks Free Edition signup page and pick your preferred signup method Databricks Free Edition | Databricks on AWS
    2. Access free training: Free unlimited access to training content on Databricks Academy provides on-demand learning experiences for all skill levels Databricks Launches Free Edition and Announces $100 Million Investment to Develop the Next Generation of Data and AI Talent – Databricks
    3. Join the community: Connect with other learners and experts
    4. Start with sample datasets: Practice with built-in datasets before using your own data

    The great news is that all self-paced training across AI, data engineering, and more is now free for learners Databricks Training & Certification Programs | Databricks, making it easier than ever to get started with Databricks!

  • Getting Started with the MSSQL AI Agent in VS Code

    Recently I was working in VS Code and I saw a walkthrough for the new Copilot chat features. I decided to give those a try in trying to get some information from my SQL Server instance.

    This post walks through a few things I did with this GenAI agent. There is a video walkthrough at the end.

    Note: I have copilot access set on VS Code as a part of my employer’s benefit.

    This is part of a series of experiments with AI systems.

    First Steps

    When I start VS Code, I see something like this.

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    One of the Walkthroughts recently mentioned copilot. If I click the “More” at the bottom right, I’ll get this image. You might see something different, but Id’ expect you have a Copilot walkthrough if you can use Copilot. I choose the 4th one down (where the mouse pointer is).

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    This opened a Copilot pane. There were a few items, and you can see on the left in the image below, some have checkmarks. I’d explored these before.

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    If I scroll up, I see the one I wanted to get, which was “chat about your code”. I picked this one. This opened a blade to the left when I clicked the blue “Chat with Copilot” button.

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    I had read there are these @ agents (look up at the right side) and decided to type “@”. I saw a list of things.

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    Lots of places to work, but I choose the @mssql agent, since this is the place I tend to work. In the lower pane, I typed a question.

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    Above this (still in the left blade), I got a response.

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    Below this, I got some text and code explaining how to access a list of databases on various platforms. Not sure why MySQL is first, but I’m assuming this is alphabetical. For SQL Server, I saw this. This is a reasonable answer, with some help on how to execute it.

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    I then decided to connect to my local instance. I have the MSSQL extension, so I clicked that and got a connection.

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    Rerunning that query produced the same response. However, when I opened a query window, I got different results. Note the little database icon on the left, below my prompt, with “Untitled-1” next to it. This is the context, which I also saw added to the lower prompt box, just above where I would enter a prompt.

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    However, this didn’t work.  After a few minutes,  I got this.

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    and this. The LLM is trying, but can’t seem to get a query to run. It did try.

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    I then decide to move on.

    Getting Results Back from Questions

    This isn’t really the type of thing I’d do, but I decided to try and get some info from a database. The one above isn’t that interesting, so I switched to asking the model some questions. Here’s the first one, where I don’t remember the exact table name, but I ask.

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    It’s queried the database, and there isn’t a player table. However, it continues to look and finds dbo.players.

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    Even better, once it has the answer, it also provides a little more info. Maybe good, maybe bad. This reminds me of talking with a person that gives me more information than I asked for.

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    I try something else. Let’s get some metadata, since I clearly don’t remember what’s in this database.

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    I get a nice response, with some guesses about what information is contained inside these tables.

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    OK, can I query for information. I’ve always been a bit more of a hitter than a pitcher, so I’ll ask a question. This isn’t asking to join specific tables, but get me an answer.

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    It worked, though to be fair, I tabbed over to SSMS and wrote this query in the same time (with SQL Prompt) as the Copilot agent. Cool to see as I’d forgotten Thome and Vlad were up there.

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    While I got the answer, I didn’t get the query. I asked for it and got it, with an apology.

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    I’ll do something else. Who played the longest. Might be a somewhat funny query to write for a quick answer. I’d have to join a few tables and look for a sum.

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    It likely remembered I wanted the query, so that was included, with an explanation. However, it only looked at the batting table.

    I asked other questions about fielding and pitching and got those answers (Nolan Ryan, 27 years with fielding stats and pitching stats. So I asked that:

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    Below this, I see the two players who tied, which Copilot noted.

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    The code provided only returned one player. I checked, which is something that you should always do. I asked if I could get better code. I got a few options, and I liked the RANK one, so I tried it and it worked.

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    Slightly annoying, but when I think about this type of conversation with someone else, especially a junior dev, I might have the same results and iterate this way.

    At this point I also asked about databases, and I got a result. Maybe I needed a query to run first? Not sure why this works now.

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    Summary

    This was an interesting set of things I could get done with this agent in VS Code. It’s not amazing, but it was helpful. I could tackle some light query tasks or db query ones while also handling some other work. In this case I wasn’t in the zone, trying to code or decode a database schema. Instead, I had a few things to try, and I let the agent work while I tabbed over to close some emails and chats.

    In a job where I might need to find info from an unfamiliar database, this could be helpful in getting things done, though it’s hard to know if it’s slower for me if I were focused on ths all the time. The agent can find some info without me, but it also failed in a few cases. I started to try and get other things done when I noticed delays in responding and some hung queries.

    Learning to use an AI agent to help you is a skill, and it’s one that takes time to develop.

    I’ll look at some more practical tasks in the next post.

    Video Walkthrough

    Here’s a video walkthrough of most of the stuff in this post. It differs slightly as working with LLMs is not deterministic.

  • Advice I Like: Praise

    Don’t reserve your kindest praise for a person until their eulogy. Tell them while they are alive when it makes a difference to them. Write it in a letter they can keep. – from Excellent Advice for Living

    This is something I try to do more. Not the letters, though that’s not a bad idea, but I find myself reaching out with short messages or thoughts (text, FB, etc.) to touch base with people. Friends, sometimes people I see often, sometimes people I see rarely.

    In either case, as I age, I realize life is getting shorter and I ought to try and ensure I communicate more with people I care about.

    I I’ve been posting New Words on Fridays from a book I was reading, however, a friend thought they were a little depressing. They should be as they are obscure sorrows. I like them because they make me think.

    To counter-balance those, I’m adding in thoughts on advice, mostly from Kevin Kelley’s book. You can read all these posts under the advice tag.

  • Using Customer Docker Compose File Names

    As I use containers more and more to run various things, I decided I not only wanted to set up docker compose files, I wanted to name them something other than docker-compose.yml. While I often have these running in separate folders with separate batch files to start them, I wanted to have the name mean more.

    This post shows how to do this.

    Creating the File

    Obviously the name is the only change. All the other items in your file need to match. For me, I created a new file with YML in it, which looks like the image below. I then saved this as SQL2025.yml, which is the version of SQL Server this container runs.

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    There’s nothing magic here, so I ran this:

    docker compose up –d sql2025.yml

    That didn’t work. I got docker errors, so I had to search and got a Google AI summary (which I don’t like) that noted there is a –f parameter. I tried this.

    docker compose up –d –f sql2025.yml

    That didn’t work either. I clicked through on Google to the docs, and I see the –f. However, I noticed that the –f comes before the command.

    I then changed this to

    docker compose –f sql2025.yml up –d

    and things ran. Of course, I needed to alter my “stop” command below, as you can see.

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