This is NOT a production ready solution, in fact I would not even recommend that you try it. I definitely wouldn’t recommend it on any machine with anything useful on it that you want to use again. We will be using a re-compiled dockerd.exe created by someone else and you know the rules about downloading things from the internet don’t you? and trusting unknown unverified people? Maybe you can try this in an Azure VM or somewhere else safe. Anyway, with that in mind, lets go.
That’s the kind of intro that makes me want to try it out.
Part of that announcement was them talking about the Common Data Service. When I first heard about CDS months ago, I was again confused. It sounded like some weird semantic layer for the data in Dynamics CRM. Maybe useful if your data lives in Dynamics 365, otherwise who the heck cares.
Oooooh boy was I wrong. Microsoft is aiming for something much, much more ambitious than an awkward pseudo-database layer for people who don’t like SQL. They are aiming for a common shape for all of your business data. They want to want to create a lingua franca for all of your business data, no matter where it is. Especially if it’s hiding in Salesforce.
Now, do I expect them to succeed? I’m not sure. I’ve learned the hard way that every business is a unique snowflake, even two business in exact same industry. But if anyone can do it, Microsoft has a good shot. They’ve been buying up CRM / ERP solutions for decades.
There’s some good stuff in here, including the realization that Power BI is not strictly intended for database developers.
The latest addition to my recent series of DAX based games is the classic Minesweeper game. This is the game where you are presented with a 9 x 9 matrix of squares. There are 10 hidden mines and you can either step on a square or place a flag where you think there might be a mine. If you are lucky enough not to step on a square that contains a mine, you will get clues that help you identify where the mines are.
Click here if you would like to see the final publish to web version.
Click here if you would like to download the PBIX version to go through the code.
In this post I’d like to show you a little something to demonstrate how we can integrate one of these modules into SQL Server and just how powerful this can be.
This is really just for fun and it may not really be something that you’d want to put out into production but when I happened to notice that there’s a Python module that interfaces with Google Translate, I wondered to myself if it’d be possible to write a procedure that could take a string and automatically translate it into our native language.
There are a couple of setup steps but once you get past them, it’s easy going.
While writing a sample random function in using T-SQL Server, I have remembered, why not write a job title generator for T-SQL domain only. You might have seen so called bulls**t job title generator and similar, but this one is T-SQL SQL server specific.
So, why not come up with random, yet funny T-SQL job titles. And making it, I have to tell you, it was fun. And I was simply hitting that F5 button in SSMS, to get new job title generated and laugh out loud.
It took me a few clicks, but I got “Qualitative R ggplot library Stackover subscriber,” which might be hitting the mark a little close.
Democratized artificial intelligence is one of five trends driving Gartner’s latest Hype Cycle for Emerging Technologies, which it updates this month, as it traditionally does during the month of August.
The analyst group took a slightly different approach with this year’s Hype Cycle for Emerging Tech and grouped the 35 individual technologies into major groups, which includes digitalized ecosystems, do-it-yourself biohacking, transparently immersive experiences, and ubiquitous infrastructure, along with democratized AI.
The five trends will “blur the lines between human and machine,” Gartner says. “CIOs and technology leaders should always be scanning the market along with assessing and piloting emerging technologies to identify new business opportunities with high impact potential and strategic relevance for their business,” writes Mike J. Walker, research vice president at Gartner.
We could give it some smarts. For example, we know that in our game, we can only choose X or O, so we could put a data constraint on the Play column. And we know that in our game, you can’t play on the same space more than once, so we could put a unique constraint on the combination of GameID and Position. You could even be really creative and enforce our game’s alternating player moves by putting a data constraint on the Player column such that it equaled 1 when (Turn Modulo 2) equaled 1 and 2 otherwise. (Really it wouldn’t need to be a data column at that point, just a calculated column.)
But imposing those restrictions robs our data structure from its raison d’être. It’s no longer a general purpose game play storage system; it only works for our game.
Instead of saddling the data storage itself with all of those rules, we could enforce all of the game mechanics through our data interpretation and manipulation logic. When we saved a game move, we could make sure that an X or O was played and it could check to see whether the specified square was already used. When we analyzed a game to determine a win, all of the criteria could be housed in that consuming query. But this flexible design isn’t done inflicting its complexity on us.
Riley covers a number of T-SQL features in the process of this post.
It turns out there’s a concept called bitmasking which can work a lot like this cardboard cut-out process. (Props to Dylan Beattie for his quick visual demonstration at NDC Minnesota which drove this point home.) First, you represent your game state with a bunch of bits (“OXOOOXXXX” yields “0100011110” for our example above, remembering that we’re padding that last 0 just to make the powers 1-based instead of 0-based) and then you represent your winning state with a bunch of bits (“0000001110” for our example winning state here). Now you use the magic of “bitwise math” to compare the two.
For our use, we want to find out whether our mask exposes the winning three bits. We want to block everything else out. With bits, to check if both items are true, you use “AND” (0 and 0 is 0; 0 and 1 is 0; 1 and 1 is 1). If we apply that “AND” concept to each bit in our game, it will squash out any values which don’t match. If what we have left matches the mask (fills in all of the space we can see through), then we have a match and a win.
The twist in all of this is that the end result doesn’t quite work as expected, but it was interesting watching the process. That said, there’s a good reason why we don’t use T-SQL as a primary language for development…
Luckily, this syntax also happens to be SQL syntax, so we’re almost done. So, let’s try plotting this formula for the area of x BETWEEN 0 AND 105 and y BETWEEN k AND k + 16, where k is just some random large number, let’s say
Unfortunately, most SQL databases cannot handle such large numbers without any additional libraries, except for the awesome PostgreSQL, whose decimal / numeric types can handle up to 131072 digits before the decimal point and up to 16383 digits after the decimal point.
Yet again, unfortunately, even PostgreSQL by default can’t handle such precisions / scales, so we’re using a trick to expand the precision beyond what’s available by default.