CloudDat Monthly High Capacity

My main use case for CloudDat  is storing, processing, and analyzing data. At my project and company, we use platforms like AWS  instead of some servers. This really helps when data is handled in real-time. CloudDat 's real power comes into picture in real-time scenarios where anyone can use cloud in a very safe way. Cloud is basically referred to as a more secure method. That's where in the real-time scenario, we use it.

I work in healthcare as of now, so my scenario with CloudDat is more into wearable devices. For example, for any patient, they have to check heart rate or any oxygen level. We have scenarios where we have wearable devices to stream patients' vitals. For that, we use these data flows in a cloud dashboard where doctors generally use this data flow, and that really benefits the health risk of that particular patient.

As of now in the health industry, this is one of the examples where I really come into the picture, and I have hands-on experience with CloudDat. I don't think I have any other good example other than this.

The best features CloudDat offers are very good. In real-time, it gives us a cloud platform where the data pipeline for real analytics is used. Some features I used include ones that helped me in healthcare IoT, and also examples into scalability, where anyone can handle this data in a cloud, and even if it doesn't go down, there won't be any downtime. Since it is a cloud platform and it is very fast for deploying any new feature, that is one of the best things which I have come into hands-on.

Using CloudDat has positively impacted my organization with more scalability for a long term. Handling became very easy for each user, and any kind of data, any large amount of data can be handled with different users in no time. I have come across a few things including more flexibility. Flexibility in the sense it supports both short-term and as well as long-term growth plans, where if you want to integrate any data through cloud, that can also happen. That's one of the good features which we experienced.

Improvement-wise for CloudDat, I think some days there is some latency. The scaling must be fast enough, but sometimes it avoids delays. That is one challenge we had. Sometimes the server might be down and there would be some downtime. That is one thing which we had a challenge with. When you use any policies, particular policies in that features, there would be some predictive analytics to improve that efficiency. It's more of having to always see what are the new features they have added and get advanced to that. That's one of the challenges we faced. In a real-time, one more thing is our project handles HIPAA, so it is always used by many users. Their scaling is also one of the features which we had a challenge with, actually.

Regarding needed improvements for CloudDat, documentation-wise, from cloud, there are certain features where you can directly download, but that would not help you actually. You have to always be updated to cloud features. There are certain versions every time it gets updated and you have to always get updated to those new features. Documentation matters from previous to new features, all that. In real-time, I maintain a documentation which ensures every time what was in past and what is present and what we can do more in the coming days so that it can be more clear so that we have anything handled in a performance way. It should be documented and it is already documented.

An improvement needed for CloudDat that I haven't mentioned yet is that it should secure more cloud dashboards to monitor patient vitals in real-time. As of now in IT, since I'm into healthcare, it generally helps with leaking risk of any particular patient's information, but in the dashboard, you will come to know everything. That's where I think it should hide. That's one feature I see which needs to be changed.

I have used CloudDat for more than two years, specifically for about two years.

CloudDat is stable.

CloudDat's scalability is very good because as I already told, it generally handles the data in the cloud. It handles data wisely. You don't need to worry more on how it is handled in a deeper way because it's all handled in a server. In a real-time, we basically handle the scalability in an upscale, where you don't need to upgrade your VMs always. It is always stored in an upscale. There are some other diagonal scaling as well, but we don't use them. There is also horizontal scaling as well that we don't come into picture with. In my company, presently we use vertical scaling and all that.

When I say scalability with CloudDat, it basically helped me handle millions of data without downtime, where I handle a lot of data. Whenever I create any data in the cloud, that is stored in that particular server. At a time, any other user can access that data which I have stored in the cloud. The scalability is very good with CloudDat. It doesn't shrink any kind of data and it ensures the performance and the data is more accurate and more efficient. That's where a real-time picture comes into picture. It's very long, it's very planned, it's very expected data.

Our customer support for CloudDat is okay. There is a support which generally supports based on the ticket raised and they generally come and schedule a call for what is more detail of asking what the requirement or what is the issue. Based on that, the support is always given. That's really good that the support is there.

I did not previously use a different solution before CloudDat, but my company seniors earlier were using a different project, a different cloud rather than AWS . So there was Azure  and also there was Microsoft. They have used certain other features and then at last, they brought in CloudDat. Earlier it was different.

I think I have seen a return on investment with CloudDat because it really helped save a lot of time. The cloud platform enables different users. That's very useful and the data is always stored in the cloud. That's more of time-saving.

Before choosing CloudDat, I evaluated other options such as Microsoft Azure  and Google Cloud  Platform. These were two they had chosen earlier, but again, they thought that CloudDat is the best one. They came in a real-time to choose CloudDat.

I can share specific outcomes related to time saved with CloudDat. You don't need to always access it each time. If a user can have multiple access to a particular cloud, then he can run in multiple projects and that really helped each candidate or each person to access a cloud and save their time. Time-saving is one of the most crucial and one of the best features over here in CloudDat.

I would definitely say if you are using CloudDat where you need everyday data in a cloud and you want to use something, especially storage level where you have a lot of data, unlike other industries, especially when you are into healthcare and all that, instead of buying new servers, CloudDat helps you a lot. That's what my experience is. Regarding CloudDat's AI capabilities, I think its governance and security is very good, actually. Cloud has enabled those features in the platform where you don't need to worry about the governance. They always give a stable data where it's always protected and it's sensitive data, especially in my healthcare, it's a sensitive data. Whenever you download anything, it is not passed to anyone. It can be only downloaded from a particular user and it can be used in a real-time for that particular person. Governance  and security-wise, it's very true. There won't be any leakage of any data, especially for the sensitive elements. It's very reliable towards what we need in the market.

Regarding CloudDat's AI capabilities, accuracy is also very good here. AI things should come more into picture in CloudDat. As of now, it handles a few things including continuous integration, it helps through the cloud. Some other features it handles include always maintaining some policies where you have to always continuously follow that. Cloud settings also plays a different role over here. These are more points which I have in a real-time.

The features of CloudDat, basically, since it's cloud, it is very secure. It is also more reliable where it has handled a lot of encryption of data. It identifies who is accessing the particular data in the cloud, including entity management, all that. Sensitive information would be there at my healthcare industry. We always give access to limited users. The scalability is quite important as well as it's more reliable. Data protection is more important at my present company and which the cloud handles. Some compliance and governance also it handles, where it is more accountable towards who handles that particular data and what kind of regulatory it handles. We handle more HIPAA files, so that is one thing.

The cloud provider I use for my hybrid cloud setup is AWS. I choose eight out of ten for CloudDat because it handles more in a cloud way, and it uses AWS server and all that. There are other tools in the market where it handles different clouds. Advanced tools are also there in the market. I would rate this review as an eight out of ten overall.