The global data cloud is growing and doing so at an ever-increasing rate. In fact, it’s being predicted that the “global datasphere” is going to hit 175 zettabytes by 2025. How much is that? Enough for a few lifetimes of HD movies.
Naturally, as the datasphere gets larger, so does the task of managing and securing it all. We’ve remarked a few times in this space how cloud computing, while already growing before COVID, has exploded, driving the construction of new servers all over the country and the increased adoption of new cloud-based programs like Zoom, which has gone from obscurity to a household name nearly overnight.
The rise of the cloud has also created opportunities for those with an entrepreneurial spirit. Without the need to develop and maintain massive server racks themselves, a startup with access to a desk and a laptop can compete in a number of different spaces that would have been impossible before. Now someone in a developing country can access cloud computing resources to develop a new program and use another resource to develop an app that will allow anyone anywhere with a data connection to make use of that program. This fact has led to the rise of many of these kinds of startups which in turn have been one of the major factors driving the increase in data usage.
While this has created certain challenges, the benefits have been clear. Cloud computing allows companies to scale up or down quickly as needed. Rather than having tons of electricity-sucking servers stored in the basement that may be too much or not enough from one week to the next depending on the projects going on at the time they can easily scale up or down based on demand. That saves a lot of money since you only have to pay for the server space you actually need at any given time. You need less, you pay less. You need more, you pay more for only as long as you will actually make use of it, instead of buying all that equipment for what is only a temporary need.
In terms of the challenges, security is probably the most significant. Yet, elegant solutions have been developed in that realm. Private companies and even individuals are able to access encryption that would give the NSA a hard time. Yet, a simple password can decrypt it so that you and whoever you want to share it with can access your information with ease.
That’s the basic model that TARTLE uses. Our data marketplace is hosted in the cloud, using encryption that protects your data in such a way that only you and whomever you sell it to (or choose to share it with, whichever you choose) can access it easily. This creates a balance between security and fluidity that everyone can benefit from.
Normally, we talk about how our system is something that individuals can financially benefit from. However, there is no reason companies can’t benefit from selling or sharing data in the TARTLE data marketplace as well. After all, it is guaranteed that someone out there would benefit from incorporating your data into their models, and vice versa. Companies that join TARTLE as sellers and buyers could arrange a mutual exchange of data that would allow both of them to improve their operations, which they could then learn to better interact with the individual sellers of TARTLE to further refine their data sets.
This creates a snowball effect in which data begets more data. However, rather than just piling up uselessly in a server somewhere it is constantly getting analyzed and refined and used ever more efficiently to drive more efficient businesses which in turn can lead to better lives for their employees and their customers.
What’s your data worth?
The global data cloud is growing and doing so at an ever-increasing rate. In fact, it’s being predicted that the “global datasphere” is going to hit 175 zettabytes by 2025. How much is that? Enough for a few lifetimes of HD movies.
Speaker 1 (00:07):
Welcome to Tartle Cast with your host Alexander McCaig and Jason Rigby, where humanities steps into the future, and source data defines the path.
Alexander McCaig (00:24):
Jason, can we talk about the obvious?
Jason Rigby (00:26):
What, global datasphere?
Alexander McCaig (00:28):
Yeah.
Jason Rigby (00:28):
And how by 2025, it's going to be 175 zettabytes.
Alexander McCaig (00:33):
Zettabytes can you [inaudible 00:00:34].
Jason Rigby (00:35):
Zelda.
Alexander McCaig (00:36):
Yeah Zelda. Ocarina of time Creek game, Call of the Wild also another good game.
Jason Rigby (00:42):
Mm-hmm (affirmative).
Alexander McCaig (00:42):
Can we just we'll explain for some context how much size this is? Because people enjoy this. Can you just read that whole sentence?
Jason Rigby (00:50):
Yeah. For context, Zettabyte translate to roughly a thousand exabytes are 1 billion terabytes or 1 trillion gigabytes.
Alexander McCaig (01:00):
Okay. So-
Jason Rigby (01:00):
A petabyte or 1 million gigabytes equates the volume more than 3.4 years of 24/7 full HD video recording.
Alexander McCaig (01:08):
Yeah. So zettabytes is 1 trillion gigabytes.
Jason Rigby (01:10):
Mm-hmm (affirmative).
Alexander McCaig (01:11):
That's a lot. That's a lot. It's a lot of space. And so 1 trillion gigabytes and how many zettabytes of the same is going to be 23.4?
Jason Rigby (01:20):
No, 175 zettabytes.
Alexander McCaig (01:23):
Okay. So 175 trillion, gigabytes.
Jason Rigby (01:30):
So they said multiply that capacity by 1 million. And that gives an idea of where a global Data usage is heading.
Alexander McCaig (01:34):
Yeah. Okay. So safe to say that it's a huge incomprehensible size that doesn't make sense to a human's brain, but when you have something that's growing that much, you got to find an effective way to store it. And so you have cloud data storage centers and by having something like that, it offers benefits for people that are data researchers.
Jason Rigby (01:55):
Mm-hmm (affirmative).
Alexander McCaig (01:56):
Okay. And they break down into a couple of categories here. The first one is, I don't have to rely on my computer and its little itsy bitsy processor to do something that tens of thousands of server racks with their own processing chips and GPU's, can do themselves. So if I'm a research and I'm like, man, I really want to deal with this model. I remember when the early days of Google earth came out and I'm like trying to get this thing. [crosstalk 00:02:25] They're like the zoom.
Alexander McCaig (02:30):
And I'm like, show me a secret base show many secret base. And then, but you know, it's like trying to render this globe, but now what we can do is we can rely on all that stuff to be processed somewhere else.
Jason Rigby (02:43):
Right.
Alexander McCaig (02:44):
Say for instance, you're a video editor. It's that okay with you?
Jason Rigby (02:48):
Oh yeah, that's good. How's it good for you?
Alexander McCaig (02:49):
No, it's great.
Jason Rigby (02:50):
No in my Insight, is your site?
Alexander McCaig (02:51):
Yeah, it's all good. For video editors, it takes a lot of processing time on and it like beats the crap out of your computer, but now they have all these open source frameworks and online things that you can use the cloud and its processing power to actually render your videos for you and do your editing. So all you got to do is use a web browser to go on this online cloud tool and just work with that and do nothing on your own computer.
Jason Rigby (03:16):
Yeah. And what I thought was interesting, I wonder with all this, by 2025, with that rate of growth-
Alexander McCaig (03:23):
Four years.
Jason Rigby (03:23):
Yeah. Is it going to be the same as obesity? Six, eight of the growth.
Alexander McCaig (03:28):
As data goes, obesity grows. Yeah.
Jason Rigby (03:31):
That'd be a great, good dataset.
Alexander McCaig (03:32):
It could be are people becoming more sedentary or we're creating more devices creating more time
Jason Rigby (03:35):
For those in South America, you guys got to stop eating,
Alexander McCaig (03:38):
Stop eating so much meat. Have you not realized since, large cattle operations have grown there and the cost of meat has become cheaper, your obesity rates have increased.
Jason Rigby (03:51):
Oh, South America. It's like, I think it's the worst.
Alexander McCaig (03:53):
It's bad, its bad [crosstalk 00:03:54] the data is right there telling you the cousing mood don't eat. You know?
Jason Rigby (04:00):
Yeah. And it's all the fried potatoes. And then they were showing the plate sizes and then comparing them to different countries and stuff. And it was amazing in South America. You know how large the plates were.
Alexander McCaig (04:13):
Yeah. I mean, if I go to any sort of Hoboken, New Jersey or like Jersey city, I'll go to a Brazilian place and they'll have a plate that's just enormous.
Jason Rigby (04:26):
Yeah.
Alexander McCaig (04:26):
And I'm like, what am I going to do with all this?
Jason Rigby (04:27):
Yeah. It's so delicious, but its all that for you.
Alexander McCaig (04:28):
That's totally off topic.
Jason Rigby (04:31):
I know.
Alexander McCaig (04:32):
So another thing of this-
Jason Rigby (04:33):
I just thought I would do a cool side note there. I like to keep the show exciting.
Alexander McCaig (04:37):
Let's keep it exciting.
Jason Rigby (04:38):
I'm a simpleton. So I have to keep it. And I like to be funny sometimes.
Alexander McCaig (04:46):
Yeah.
Jason Rigby (04:46):
So I have to keep, if we just talk about data and clouds. [inaudible 00:04:50].
Alexander McCaig (04:50):
No, it's a drag. [crosstalk 00:04:52] I was a crew to the benefit of humanity.
Jason Rigby (04:56):
I want you to know they said this, you can not separate cloud computing from data science.
Alexander McCaig (05:01):
Well, you can, but is it effective for you to do so? No.
Alexander McCaig (05:06):
And another benefit to this, if you're doing data science or anything that's processor heavy, you don't have to build a huge infrastructure to support this thing in sort of a local environment. If you're okay with having your stuff online in a decentralized format, somewhere else managed by a cloud infrastructure. And that's okay with your security protocols, then use it. I mean, some of our new observatories, like the Rubin observatory we talked about, that's what they're moving into.
Jason Rigby (05:31):
Yes.
Alexander McCaig (05:31):
Totally cloud computing. They're relieving the stress and costs of having an infrastructure specifically at site, by a telescope and saying, "we'll just use what Google has." And then on top of that, you have a lot of other benefits with this thing called auto-scaling. So, I'm only going to pay for the amount of processing that I need and it can fluctuate anywhere in between. So the variable pricing models become much more effective for researchers, especially when they only have grant funds.
Jason Rigby (05:59):
Yeah. And what they were talking about, what I thought was interesting is when we're expanding the role of the cloud is the amount of data continues to grow. So securely storing the data in a practical cost, effective manner has become a priority. So, I mean, we talked about the data centers and the reads, and how they're investing in all this. But really when we look at a decentralized approach to the cloud and all this colossal data loads, when we look at that, it's like, what does the future look like for that?
Alexander McCaig (06:27):
Yeah. So I think the future looks like the model we use a Tartle for encryption Sanders. We have a lot of very private, sensitive information and making sure that we can't read it and other people who try to access it, can't read it is important, but it can't be so slow that it burdens the system down trying to decrypt these things. So..
Jason Rigby (06:48):
Yes.
Alexander McCaig (06:49):
We've adopted, encryption standards that prevent us from looking at it and only when an individual chooses to open up or decrypt that information, they do so. So like trying to attack our servers from the outside without actually facilitating a transaction and getting the okay, a user, when you're doing this, they have to physically decrypt by putting in like a passcode, like four digits. And that actually decrypts your data in the system for a specific time limit, but it's not burdensome. It's not burdensome us. It's not burning out on them, but it's an effective way for dealing with large amounts of data that are very private and allowing us to store it effectively and being able to access it effectively for whoever that might be, that needs the access.
Jason Rigby (07:30):
I think why I'm so pro with this and why I'm getting excited about this, it goes right along with our philosophy of Tartle in the geopolitical sense with emerging markets, we're looking at it levels the playing field.
Alexander McCaig (07:42):
Oh yeah.
Jason Rigby (07:43):
So, it's not like, okay, I need to have this $10 million data center and all these racks of servers to be able to compete. Now, a guy on a laptop in Bangladesh can compete just as well as somebody that's in Montreal.
Alexander McCaig (07:59):
Yeah. So lucky for us we have these servers that are supporting this cloud infrastructure and we've applied that to a tool where you can use it on a cell phone, or a laptop or a tablet. And so the access is just huge. It's large decentralized access that works agnostically across any sort of system talk about leveling the playing field. And we have such great storage and encryption practices that... How do I put this? It becomes very difficult to take something that's not yours.
Jason Rigby (08:34):
Right.
Alexander McCaig (08:35):
And so it's more conducive for people, housing truthful information and putting things in there that they otherwise wouldn't put somewhere else. They feel comfort and safety doing so.
Jason Rigby (08:45):
Yeah. And I think another part that we're not looking at in a perspective of understanding this is that, when we start looking at the cloud, then these provide tools. They are in competition, so they're going to incentivize the user. And so you have different software. You're going to have artificial, intelligent tools, analytic tools, data visualization tools, all of these things are going to try to attract you as a buyer. So it's not just the storage aspect of it. There's going to be these other, like data visualization is huge.
Alexander McCaig (09:18):
Yeah.
Jason Rigby (09:18):
If I'm doing a Ted talk, I want to make sure I have..
Alexander McCaig (09:22):
Visuals.
Jason Rigby (09:23):
Yeah. Visuals.
Alexander McCaig (09:24):
This reminds me of data storage has become a commodity.
Jason Rigby (09:27):
Yes. Yeah, exactly.
Alexander McCaig (09:28):
So, if you go to like an Exxon station, I don't know if you have it. I don't usually like going, cause it's more expensive, it's ridiculous. Cause its gasoline, we've making it forever. [inaudible 00:09:37]
Alexander McCaig (09:38):
But they say, Oh, we've added, we have additive stuff into the gasoline to clean your engine. It's the same thing that what's going on with cloud computing, everybody and their mother has a cloud computing center with server racks. Now it's like, what little bit of source software? What sort of additive can we put on there to make your engine more efficient? Does that make sense?
Jason Rigby (09:57):
Yeah. And when we look at cloud computing and we look at the three different types of data, we have to understand that there's structured data semi-structured and then unstructured. And we talked about the Lake house with that-
Alexander McCaig (10:07):
Yeah.
Jason Rigby (10:07):
Dealing with unstructured data. But when we look at these three and then the silos and then the databases that each company has when these three levels, that's the problem. They don't know what to do.
Alexander McCaig (10:18):
Yeah. They don't know what to do with it. And they're not incentivized to move it.
Jason Rigby (10:20):
Right.
Alexander McCaig (10:20):
So a nice beneficial tool is like, okay, if we put it on a cloud computing, a cloud storage system, it's way more flexible. It's transient, it's more fungible for us to move it back and forth. And then if you incentivize them to say, Oh, let's open up a data stream with this. Some more stuff through Tartle, or sell our data through Tartle. That seems pretty beneficial. And now we don't have a locked up in a silo. We can effectively move from place to place.
Jason Rigby (10:45):
Yeah.
Alexander McCaig (10:46):
The access becomes flexible so I can set up shop anywhere in the world. I don't just have to have it here at the company. And just like, hop in through some weird local VPN. It's like, I can be in Deutschland. I can be in Brazil, Eating all those steaks or I can be, in Washington state.
Jason Rigby (11:02):
Well tartle can become kind of SAS based because then it can become another tool that that company can use when they become a part of this cloud organization-
Alexander McCaig (11:09):
As they should be doing.
Jason Rigby (11:10):
Yeah. We're just another tool that helps you. Yeah. Take that, semi-structured and unstructured data and then, or even your structured data and then be able to go to those people and ask the right question.
Alexander McCaig (11:22):
Yeah. And then improve upon your datasets. And then after you've improved it, you can go back and resell them.
Jason Rigby (11:26):
Yeah. And then the data scientists can come and say, Oh, okay, we have these questions, we've gone through and we've sifted through the data and here's where we're at. And here's where we're stuck. So let's use Tartle to answer these questions.
Alexander McCaig (11:38):
Yeah. You remember you ever seen the movie Spaceballs?
Jason Rigby (11:40):
Yeah. A long time ago. Yeah.
Alexander McCaig (11:42):
And we're in there combing the desert. And that's what I think about with the data scientist.
Jason Rigby (11:47):
Yeah. That's kind of the same.
Alexander McCaig (11:49):
Have you found anything yet? We've found shit.
Jason Rigby (11:52):
Yeah, exactly. Yeah. And then it's so gleaning insights from data. It's kind of one of those mystery, it's like these data [crosstalk 00:12:06]
Alexander McCaig (12:07):
What's the occult side. Exactly. [crosstalk 00:12:09].
Jason Rigby (12:09):
The data scientists, they're almost taking this mumble jumble and then they go to C-suite and say here's our... We come from, they have like, ah, we are here...
Alexander McCaig (12:19):
They are robbed up. We've had a seance.
Jason Rigby (12:21):
Yes.
Alexander McCaig (12:22):
And this is what the data spirits have told us.
Jason Rigby (12:24):
Aka a hunch.
Alexander McCaig (12:26):
We have a hunch, and...
Jason Rigby (12:28):
Here's where you should take millions and billions of dollars and put it towards this way.
Alexander McCaig (12:32):
And the C-suites like, that's ridiculous. Go sign up on Tartle.
Jason Rigby (12:36):
Exactly.
Speaker 1 (12:44):
Thank you for listening to Tartle Cast with your hosts, Alexander McCaig and Jason Rigby, where humanity steps into the future, and source data defines the path. What's your data worth.
