| Read the transcript below: | Hello and welcome to Take Five with Automation World. I'm David Miller, Senior Technical Writer for Automation World. This week, I'm going to discuss the use of cloud computing in industry. As many watching this program probably know, it seems like more and more organizations are moving into the cloud by the day. And it doesn't seem like that for no reason. The data supports it too.
Looking at the numbers, the public cloud service market is expected to reach $623.3 billion worldwide by 2023. According to Grand View Research, it's expected to grow at a compounded annual growth rate of 14.9% from 2020 to 2027. In 2021 alone, cloud infrastructure is expected to grow by 35%.
So when we talk about the cloud, what we mean is simple. Essentially, we're referring to the use of networks of remote servers, accessed over the internet to store, manage, and process data. This is in contrast to having an on-premise server, which would be more commonly accessed via a local area network, and will require a company to own the actual physical infrastructure of that server.
Now you might be asking, "What's all the fuss about?” But the fact of the matter is, there are a lot of reasons that this shift is happening. Cloud has many benefits to offer companies, industrial and otherwise. For one, the cloud makes remote access a lot easier. Obviously remote access has been on the rise for some time now. But as I'm sure I don't need to tell any of our viewers, it became an absolute imperative when COVID-19 hit. So you can really imagine how difficult it would be for workers who were siloed off in their homes to access and collaborate via a remote server were it not for the cloud. So not only would it require finagling from IT, things like that, but to open up those local area network servers for the broader internet potentially without the proper expertise could also entail huge security risks.
On top of that, of course, the cloud provides a single source of truth, and that's vital to all kinds of remote collaboration. For instance, these days, we see many organizations who are looking to synchronize data from disparate systems in order to plan jointly across numerous facilities, or perhaps even across numerous organizations. So this type of end-to-end visibility would be almost entirely impossible without a central cloud server that could take in and consolidate all that data in real time.
So the other really significant benefit we see from cloud servers is simply that they provide greater storage capacity. These days, huge amounts of data are coming out of plants in the hope that mining and analyzing that data will help manufacturers to optimize production in new ways. So with so much more data being held onto, you can imagine how expensive it might be if one had to continually expand and maintain their own on-premise servers.
And this gets at something else, which is the capacity for cloud delivered, machine learning applications. These algorithms are trained on huge amounts of data that would be very, very difficult for a single company to furnish. And because of this, in the past, machine learning would have been seen as something that was so complicated that only the largest players could have access to it. However, many cloud services that housed the data of many, many different companies can leverage that to provide machine learning functionality in a scalable way that no single company could. So as a result, those moving to the cloud, not only having affordable means of dealing with their own data, but can tap into the value provided by others who are doing the same thing via the use of these machine learning algorithms that are being made available to them.
So in essence, what's happening is, this is allowing small and medium-sized enterprises to access capabilities that in the past simply would have been out of reach.
So that's everything I have for you today. But if you've enjoyed the segment, keep your eyes peeled for more to come in the weeks ahead.
