Maybe it was all VC funded solutions looking for problems?
It's a lot easier to monetize data analytics solutions if users code & data are captive in your hosted infra/cloud environment than it is to sell people a binary they can run on their own kit...
All the better if its an entire ecosystem of .. stuff.. living in "the cloud", leaving end users writing checks to 6 different portfolio companies.
> Maybe it was all VC funded solutions looking for problems?
Remember, from 2020-2023 we had an entire movement to push a thing called "Modern data stack (MDS)" with big actors like a16z lecturing the market about it [1].
I am originally from Data. Never worked with anything out of the Data: DS, MLE, DE, MLOps and so on. One thing that I envy from other developer careers is to have bosses/leaders that had battle-tested knowledge around delivering things using pragmatic technologies.
Most of the "AI/Data Leaders" have at maximum 15-17 years of career dealing with those tools (and I am talking about some dinosaurs in a good sense that saw the DWH or Data Mining).
After 2018 we had an explosion of people working in PoCs or small projects at best, trying to mimic what the latest blog post from some big tech company pushed.
A lot of those guys are the bosses/leaders today, and worse, they were formed during a 0% interest environment, tons of hype around the technology, little to no scrutiny or business necessity for impact, upper management that did not understand really what those guys were doing, and in a space that wasn't easy for guys from other parts of tech to join easily and call it out (e.g., SRE, Backend, Design, Front-end, Systems Engineering, etc.).
In other words, it's quite simple to sell complexity or obscure technology for most of these people, and the current moment in tech is great because we have more guys from other disciplines chime in and share their knowledge on how to assess and implement technology.
OK now you need PortCo1's company analytics platform, PortCo2's orchestration platform, PortCo3's SRE platform, PortCo4's Auth platform, PortCo5's IaC platform, PortCo6's Secrets Mgmt Platform, PortoCo7's infosec platform, etc.
I am sure I forgot another 10 things.
Even if some of these things were open source or "open source", there was the upsell to the managed/supported/business license/etc version for many of these tools.
This is the primary failure of data platforms from my perspective. You need too many 3rd parties/partners to actually get anything done with your data and costs become unbearable.
> and in a space that wasn't easy for guys from other parts of tech to join easily and call it out (e.g., SRE, Backend, Design, Front-end, Systems Engineering, etc.).
As an SRE/SysEng/Devops/SysAdmin (depending on the company that hires me): most people in the same job as me could easily call it out.
You don't have to be such a big nerds to know that you can fit 6TB of memory in a single (physical) server. That's been true for a few years. Heck, AWS had 1TB+ memory instances for a few years now.
The thing is... Upper management wanted "big data" and the marketing people wanted to put the fancy buzzword on the company website and on linkedin. The data people wanted to be able to put the fancy buzzword on their CV (and on their Linkedin profile -- and command higher salaries due to that - can you blame them?).
> In other words, it's quite simple to sell complexity or obscure technology for most of these people
The unspoken secret is that this kind of BS wasn't/isn't only going on in the data fields (in my opinion).
> The unspoken secret is that this kind of BS wasn't/isn't only going on in the data fields (in my opinion).
Yes, once you see it in one area you notice if everywhere.
A lot of IT spend is CEOs chasing something they half heard/misunderstanding a competitor doing, or a CTO taking Gartner a little too seriously, or engineering leads doing resume driven architecture. My last shop did a lot of this kind of this stuff "we need a head of [observability|AI|$buzzword].
The ONE thing that gives me the most pause about DuckDB is that some people in my industry who are guilty of the above are VERY interested in DuckDB. I like to wait for the serial tech evangelists to calm down a bit and see where the dust settles.
Cloud and SaaS were good for a while because they took away the old sales-CTO pipeline that often saw a whole org suffering from one person's signature. But they also took away the benefits of a more formal evaluation process, and nowadays nobody knows how to do one.
I'm not sure how cloud/saas made the CTO behavior and its consequences any better. At least on-prem if they picked the "wrong" DB / message bus / etc, you could quietly replicate to another stack internally as needed for your analytics needs.
If your data is lodged in some SaaS product in AWS, good luck replicating that to GCP, Azure, or heaven forbid on-prem, without extortion level costs.
It's a lot easier to monetize data analytics solutions if users code & data are captive in your hosted infra/cloud environment than it is to sell people a binary they can run on their own kit...
All the better if its an entire ecosystem of .. stuff.. living in "the cloud", leaving end users writing checks to 6 different portfolio companies.