Overall, I would rate it an eight out of ten. The reason why I'm cutting points is purely because they're still not applying deep learning techniques for the predictive part of the solution. They have to integrate deep learning techniques to solve some of the more sophisticated issues in the industry. My recommendation depends on the goal of an organization or a person. What they want to achieve through this tool. If they're just going for routine process analysis, they might not be very enthusiastic about it. But when it comes to technology integration with automation and developing various solutions in the company, if that maturity is present in the organization, they'll definitely take it seriously. In that aspect, I'd recommend they should use it and explore the capabilities of the tool. However, I'll advise you that it's not a one-stop solution for all analyses. You have to use other tools and solutions to get a holistic approach or direction.
Lead Engineer at a healthcare company with 10,001+ employees
Real User
Top 20
2024-07-31T12:47:08Z
Jul 31, 2024
Users need basic training to use the tool. They must know how to add tags and how to build things. I am a consultant for an oil and gas customer. They have Seeq, and they give us remote access to their server. We provide support. I will recommend the solution to others. It provides more options for scatter plots. They are very useful. We only analyze x and y in scatter plots. If there is a flow, I can add two or three tags to correlate them simultaneously. These options are very useful. Overall, I rate the tool an eight out of ten.
Seeq is accessible to anyone, although some prior experience in data analysis can be beneficial for more complex tasks. The predictive analytics features have been instrumental in catching excursions early, allowing us to monitor conditions proactively and prevent issues from escalating. I recommend the solution, but I advise potential users to consider the limitations of its exporting options. I rate it a seven out of ten.
I would recommend Seeq to others in the oil and gas industry for production optimization. It’s essential for that purpose. Overall, I would rate Seeq around an eight or nine. If I had to choose a whole number, I’d go with nine.
Seeq is a tool that does not store any of your data. It will only cache the data and show it on display. Whether it is an on-premise or cloud version, you cannot hamper any data on Seeq security-wise. Just like Google searches for information from the website, Seeq will buffer the information from the historian and display trends or values. The solution does not have much of a data breach or safety issue. Seeq is not a tool that requires a programming background. It's just a point-and-click tool that is for everyone. The idea behind Seeq is democratizing data analytics for everyone. You don't need to have any rigorous programming knowledge. Instead, basic knowledge of how the tools work is fine. There is something called Data Lab in Seeq, where an advanced Python algorithm is used to deploy AI and ML models. It has already been developed, but not on a very large scale. We don't know its potential yet. It has the capacity, but no one has explored its maximum potential because we are limited in our use cases. We are exploring it, and it can be deployed for a big-scale project for advanced predictions. I would recommend the solution to other users. If you want a feature, you can discuss it with the developer team. If it is a useful feature, it will be applied to everyone. They will develop this as a feature, which will be included in the subsequent releases of Seeq. Seeq is evolving by hearing a lot from the audience. Overall, I rate the solution a nine out of ten.
In terms of data integration, Seeq is outstanding. You can connect to any data source you want, making it easy to achieve connectivity. Seeq is a cloud-deployed solution with appropriate mechanisms to ensure security. One key aspect is that data flows only one way: into Seeq. Data does not come out of Seeq, so you don't have to worry about Seeq altering your data, stopping motors, or closing valves. I recommend the solution. If you are considering buying it, my advice is to get your hands on it and test drive it. However, it's important to understand that no software is perfect. If you're looking for something that meets your every dream, you'll probably not find that. But if you're looking for something complete, let me explain. Some data analytics solutions are only part of a solution. For example, they may only do predictive modeling, connect data sources, visualize data, or align things in time. Some people think those features by themselves constitute an entire data analytics package. Seeq is a complete solution. It's built for collaborative engineering, allowing others to see the work you did and share it easily. You can deploy it across the enterprise so that everyone sees the results. Overall, I rate the solution a ten out of ten.
I would recommend it to other people. My recommendation: So, typically, when there are historians, the first thing is the limitation on the number of licenses. For example, if I'm a control engineer, I have no visibility of what's happening on the quality side because quality is measured by a different team, and the systems are themselves different. You have LIMS. Now, a control engineer who is sitting in the control room has no visibility until they get feedback from the quality control group. That feedback usually happens through WhatsApp, phone communication, or physical communication. With Seeq, you can monitor and trend different data streams from different sources on a single screen. There is lot of value right here. Even though it can not be quantified in terms of cost savings. This integrated visibility adds significant value for the end consumers operating the plant. Data Integration and Cleaning: Next is the data processing capabilities, like data cleaning. Even if you are a data scientist, you may not be aware of all the algorithms available in the market. When it comes to time series analytics, it’s different. It's no longer just AI and machine learning; you need knowledge of time series data, how sensor data looks, and the applicable algorithms. Seeq offers automated, point-and-click solutions for these workflows. You don’t need to know data science or data preprocessing algorithms. Just click, select the parameter, and you’re done. Faster Time to Value: These are a couple of points where I see a lot of value. Customers often try to set up their own digitalization groups and build everything on their own instead of buying Seeq. They might try to develop or reinvent the wheel, which never happens. Everything remains in Python. If that effort is spent on Seeq, they can start developing and realizing value in the first month, not in the span of years and weeks. Overall rating: Overall, I would rate it a seven out of ten. And the reason is, Seeq was great five years back when there was no competition and digitalization was just emerging. Now, other companies are developing products like Seeq, and some features could be better and more efficient. Seeq needs to stay competitive by understanding customer expectations, which will keep changing. Seeq needs to conduct surveys and incorporate critical features and customer expectations into their product development roadmap.
Supply Chain Analyst at a manufacturing company with 10,001+ employees
Real User
Top 20
2024-05-21T14:18:16Z
May 21, 2024
My advice/recommendation depends on the kind of problem the user wants to solve. If the problem is to find a reporting tool, there are a lot of tools on the market. It completely depends on the problem the user is going to solve. I cannot simply suggest if you should use Seeq or not. First, you have to know what you are using it for and why you are using it. I would recommend it as an advanced analytics tool for processing different manufacturing data. It's easy to learn to use Seeq, but you need to have some knowledge of analytics or process engineering. Otherwise, with anything you learn, you have to give some time to the software. Overall, I would rate the solution a seven out of ten. It's a great platform, a very powerful platform to work with. We can add a lot of machine learning stuff and customize the data in Seeq. But they need to improve in a few areas, like the reporting part and customizing the dashboard. Seeq can improve those in future upgrades. Currently, there are a lot of powerful tools on the market similar to Seeq.
Based on my experience, I recommend using Seeq, especially if you need to visualize and monitor real-time data. I rate the overall product an eight out of ten.
Solve problems faster with the Seeq Industrial Analytics & AI Suite.
Data is hard, so we made Seeq easy. Purpose-built for time series manufacturing data, our software takes mere minutes to install, has easy-to-use features, and supports all phases of manufacturing analytics from connecting to your data to cleansing and reporting, so you can use your data to quickly identify trends, find answers and act on them.
Overall, I would rate it an eight out of ten. The reason why I'm cutting points is purely because they're still not applying deep learning techniques for the predictive part of the solution. They have to integrate deep learning techniques to solve some of the more sophisticated issues in the industry. My recommendation depends on the goal of an organization or a person. What they want to achieve through this tool. If they're just going for routine process analysis, they might not be very enthusiastic about it. But when it comes to technology integration with automation and developing various solutions in the company, if that maturity is present in the organization, they'll definitely take it seriously. In that aspect, I'd recommend they should use it and explore the capabilities of the tool. However, I'll advise you that it's not a one-stop solution for all analyses. You have to use other tools and solutions to get a holistic approach or direction.
Users need basic training to use the tool. They must know how to add tags and how to build things. I am a consultant for an oil and gas customer. They have Seeq, and they give us remote access to their server. We provide support. I will recommend the solution to others. It provides more options for scatter plots. They are very useful. We only analyze x and y in scatter plots. If there is a flow, I can add two or three tags to correlate them simultaneously. These options are very useful. Overall, I rate the tool an eight out of ten.
Seeq is accessible to anyone, although some prior experience in data analysis can be beneficial for more complex tasks. The predictive analytics features have been instrumental in catching excursions early, allowing us to monitor conditions proactively and prevent issues from escalating. I recommend the solution, but I advise potential users to consider the limitations of its exporting options. I rate it a seven out of ten.
I would recommend Seeq to others in the oil and gas industry for production optimization. It’s essential for that purpose. Overall, I would rate Seeq around an eight or nine. If I had to choose a whole number, I’d go with nine.
Overall, I rate the solution a nine out of ten.
Seeq is a tool that does not store any of your data. It will only cache the data and show it on display. Whether it is an on-premise or cloud version, you cannot hamper any data on Seeq security-wise. Just like Google searches for information from the website, Seeq will buffer the information from the historian and display trends or values. The solution does not have much of a data breach or safety issue. Seeq is not a tool that requires a programming background. It's just a point-and-click tool that is for everyone. The idea behind Seeq is democratizing data analytics for everyone. You don't need to have any rigorous programming knowledge. Instead, basic knowledge of how the tools work is fine. There is something called Data Lab in Seeq, where an advanced Python algorithm is used to deploy AI and ML models. It has already been developed, but not on a very large scale. We don't know its potential yet. It has the capacity, but no one has explored its maximum potential because we are limited in our use cases. We are exploring it, and it can be deployed for a big-scale project for advanced predictions. I would recommend the solution to other users. If you want a feature, you can discuss it with the developer team. If it is a useful feature, it will be applied to everyone. They will develop this as a feature, which will be included in the subsequent releases of Seeq. Seeq is evolving by hearing a lot from the audience. Overall, I rate the solution a nine out of ten.
In terms of data integration, Seeq is outstanding. You can connect to any data source you want, making it easy to achieve connectivity. Seeq is a cloud-deployed solution with appropriate mechanisms to ensure security. One key aspect is that data flows only one way: into Seeq. Data does not come out of Seeq, so you don't have to worry about Seeq altering your data, stopping motors, or closing valves. I recommend the solution. If you are considering buying it, my advice is to get your hands on it and test drive it. However, it's important to understand that no software is perfect. If you're looking for something that meets your every dream, you'll probably not find that. But if you're looking for something complete, let me explain. Some data analytics solutions are only part of a solution. For example, they may only do predictive modeling, connect data sources, visualize data, or align things in time. Some people think those features by themselves constitute an entire data analytics package. Seeq is a complete solution. It's built for collaborative engineering, allowing others to see the work you did and share it easily. You can deploy it across the enterprise so that everyone sees the results. Overall, I rate the solution a ten out of ten.
I would recommend it to other people. My recommendation: So, typically, when there are historians, the first thing is the limitation on the number of licenses. For example, if I'm a control engineer, I have no visibility of what's happening on the quality side because quality is measured by a different team, and the systems are themselves different. You have LIMS. Now, a control engineer who is sitting in the control room has no visibility until they get feedback from the quality control group. That feedback usually happens through WhatsApp, phone communication, or physical communication. With Seeq, you can monitor and trend different data streams from different sources on a single screen. There is lot of value right here. Even though it can not be quantified in terms of cost savings. This integrated visibility adds significant value for the end consumers operating the plant. Data Integration and Cleaning: Next is the data processing capabilities, like data cleaning. Even if you are a data scientist, you may not be aware of all the algorithms available in the market. When it comes to time series analytics, it’s different. It's no longer just AI and machine learning; you need knowledge of time series data, how sensor data looks, and the applicable algorithms. Seeq offers automated, point-and-click solutions for these workflows. You don’t need to know data science or data preprocessing algorithms. Just click, select the parameter, and you’re done. Faster Time to Value: These are a couple of points where I see a lot of value. Customers often try to set up their own digitalization groups and build everything on their own instead of buying Seeq. They might try to develop or reinvent the wheel, which never happens. Everything remains in Python. If that effort is spent on Seeq, they can start developing and realizing value in the first month, not in the span of years and weeks. Overall rating: Overall, I would rate it a seven out of ten. And the reason is, Seeq was great five years back when there was no competition and digitalization was just emerging. Now, other companies are developing products like Seeq, and some features could be better and more efficient. Seeq needs to stay competitive by understanding customer expectations, which will keep changing. Seeq needs to conduct surveys and incorporate critical features and customer expectations into their product development roadmap.
My advice/recommendation depends on the kind of problem the user wants to solve. If the problem is to find a reporting tool, there are a lot of tools on the market. It completely depends on the problem the user is going to solve. I cannot simply suggest if you should use Seeq or not. First, you have to know what you are using it for and why you are using it. I would recommend it as an advanced analytics tool for processing different manufacturing data. It's easy to learn to use Seeq, but you need to have some knowledge of analytics or process engineering. Otherwise, with anything you learn, you have to give some time to the software. Overall, I would rate the solution a seven out of ten. It's a great platform, a very powerful platform to work with. We can add a lot of machine learning stuff and customize the data in Seeq. But they need to improve in a few areas, like the reporting part and customizing the dashboard. Seeq can improve those in future upgrades. Currently, there are a lot of powerful tools on the market similar to Seeq.
Based on my experience, I recommend using Seeq, especially if you need to visualize and monitor real-time data. I rate the overall product an eight out of ten.