exactly

I also think conservatives have been pretty bad at communicating as well.

I've never liked Trump, but I do appreciate the good things he has done. He would have been much better off to not say really anything at all after he was elected. Many of his policy decisions have been good.

That's a far point.

*fair

I agree that there are things that he did well. As a SW architect/engineer myself, I appreciate his recognizing that we don't need to bring cheap foreign engineers here to work for less.

I think that bringing manufacturing back here is really important.

Ex SW architect and developer. Security architect and hacker (penetration tester and red team member) now.

Also used to be an aircraft mechanic.

I just think the tariff approach is not the right way.

That's one of the things he didn't do so well. I was very happy he was addressing trade deficits but that was handled poorly. On the other hand, I haven't heard any better approaches either. I personally would have probably left that one alone over cause the problems to American businesses that it did.

I have worked in just about every environment. My specialty is relational database development for very large dataset processing. I have done a lot with the Entertainment and Aerospace industries here in SoCal.

@TaLoN132, you just advanced to level 11!

So, Oracle, SQL, Hadoop, NoSQL?

I spent so much time in school learning relational models and as soon as I got out everyone started denormalizing and moving to things like elastic search and Mongo. That was fun.

At least on many of the projects I worked.

I have worked in SyBase, Oracle, DB2, SQL Server, MySQL, etc. I have tinkered with Big Data and want to do more eventually.

LOL. The only thing I used from school was a bit of C#

One of my teachers wanted to teach us Ruby on Rails, but nobody knew ruby

Haven't done a lot with SyBase or DB2 but Oracle, Postgres, MySQL, MariaDB, SQL Server I know well.

Ruby is awesome, almost as good as Python. I have to work up the motivation to learn Go and Rust. I hear those are the up and coming languages for all the new toys.

Python has been of recent intrest. Seems the only Tensorflow Keras impls.

Damn data nerds.

I have been working for quite a while on a unique problem space that is on platform that is C#, SQL, on AWS. a SAAS solution for managing intellectual property rights.

Python and R are the two defactor ML and AI languages so you will have to pick one.

Wish I had more time to experiment with other environments.

Can't say I miss writing C#.

Oh, that sounds like a fun problem. I'm just learning Azure. Have some experience with AWS, Google Cloud, and some other small providers.

Azure eh? any feedback?

I wishing banking and finance would have a big push to the cloud. It would be so much more secure and easier to manage than our on-prem stuff.

The offerings for each are nearly identical, VMs, containers, virtual networks, big data, AI and ML, relational and nosql databases, storage, hot failover, etc. It's just learning the details of whats were and the little unique issues.

*what is where

IP rights are defined by combinations of hierarchical data sets. A contract can be defined in a few hundred records, but contract processing requires comparing the cartesian sets of each in order to determine potential overlap or gaps. A single contract line item could expand to billions of rows. The resources required can be daunting.

If you are interested in playing with it Microsoft Learn walks you through the environment and lets you spin up environments for free. https://docs.microsoft.com/en-us/learn/

I change my mind, that doesn't sound like fun.

I'm quite adept at Azure 😄

I'm getting tired and must have misunderstood your comment. Again, same thing different skin. I'm honestly surprised by how similar all the platforms are. It's like they clone the same underlying architecture to some extent.

I heard rumors that they were all built on openstack but I'm not sure how true that is.

I was able to devise a way to use binary data arrays to represent the complex hierarchical relationships in a single row and discovered a math trick that lets me make those types of calculations with a fraction of the resources needed. Using traditional SQL techniques, a common query could take 1.5 to 2 hours to complete on an optimized server. I was able to get that same result in 6-8 seconds with 100% fidelity... It's not often I talk with people that will know what I am saying, so I hope you don't mind.

😄

We did a similar thing with calculations our bioinformatics department was doing on mouse DNA while I was in graduate school. Someone had written a python script to process all the data on a cluster of high powered machines and it tooks about 36 hours. We rewrote it to using CUDA and cut it down to about 5 minutes. Really just a whole bunch matrix math and graphic cards are optimized for that type of operation. I'm sure you can't share the details of algorithm but it sounds very interesting.