IBM Cloud Pak for Data on Managed Openshift (BYOL)
IBM Data and AI | 4.8.xLinux/Unix, Red Hat Enterprise Linux 8.6 - 64-bit Amazon Machine Image (AMI)
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Efficient data analysis solution
What do you like best about the product?
IBM Cloud Pak for Data has an intuitive user interface. It facilitates data analysis workflow and solution development. The service works seamlessly with Watson AI services and allows for secured connections with various data sources, whether on-premises or in the cloud. Also, it's efficient for parallel/distributed data processing and advanced data model building.
What do you dislike about the product?
I find IBM Cloud Pak for Data requires robust technical experience with IBM Cloud Services and much learning. Otherwise, there's nothing that I dislike about it.
What problems is the product solving and how is that benefiting you?
IBM Cloud Pak for Data allows my team to combine, manage, and process various data types from multiple sources to build advanced data analysis solutions for clients. It helps with data preparation, cleaning, transformation, and solution development.
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This could help the best experiance operating the console and the good for hybrid cloud platform
What do you like best about the product?
Dat ware house and cloud stores solution are the best
What do you dislike about the product?
A little bit UI experience and pricing model
What problems is the product solving and how is that benefiting you?
Higher cost for bigger projects, features the package
Excellent multicloud platform to analyze your data needs & organize your data infrastructure
What do you like best about the product?
It's a great multilayered platform that enables developers, data engineers, data scientists, business intelligence developers and data analysts to leverage services through their data. There are so many advantages of using this that many businesses have gone live with them and now maintain an integrated platform of automation capabilities. People who code in Kubernetes have heavily used this as it's easy to deploy, analyze, configure and manage the applications. The integrated testing in most cases is successful. The single intuitive dashboard that it provides is excellent.
What do you dislike about the product?
The templates sometimes get too cumbersome to customize and there are more manual steps when it comes to downtime. The RTO and RPO for when security breaches occur are significant. The disaster recovery mechanisms can be improved as they still need a lot of room and scope of improvement. Moreover, the initial setup and the infrastructure are too time-consuming and hard to understand. I feel like if you exactly know why you need this and its services for data analytics and in what kind, that is when you should think of deploying it. Starting the setup without clarity and analyzing use cases as per the organization's needs can be frustrating and challenging.
What problems is the product solving and how is that benefiting you?
IBM works with five Cloud Paks: IBM Cloud Pak for Applications, IBM Cloud Pak for Data, IBM Cloud Pak for Integration, IBM Cloud Pak for Multicloud Management, and IBM Cloud Pak for Automation. It is good to customize based on how it is hosted in our company and I feel that it gives the ability to distribute it and integrate it with multiple service vendors. We always struggled with low redundancy data storage and encryption issues as we deal with a lot of vendors at the same time. The excellent thing we scooped out of their services was the fully encrypted backup and recovery processes that they provide. That too they have multiple data centers to do that. Their data organization is good by using the IBM Cloud file storage. It is pre-confirgured and has a very highly optimized data environment which speaks for itself and provides high performance.
Great all in one tool for data
What do you like best about the product?
It is pretty easy to understand by people who are not very proficient in tech as well, and that makes it a very powerful tool.
This being a one-stop solution for your data and analytics needs, helps users in achieving optimal performance in their analytical and other tasks.
This being a one-stop solution for your data and analytics needs, helps users in achieving optimal performance in their analytical and other tasks.
What do you dislike about the product?
As containerization is still comparatively fairly new, it can be a bit difficult for everyone to understand and use it since cloud pak is mostly based on it. So, maybe if some other vertical is available for the users with lesser knowledge about it and better documentation, can help.
What problems is the product solving and how is that benefiting you?
There are several data integration challenges with a lot of data sources, cleaning and preparing the data and making it available for the analytics pipeline later on, in order to get correct analysis. Also, need to maintain the security in data on the cloud. Also, few verticals require ML and AI capabilities for different kinds of predictions as well
IBM Cloud Pak - All-in-one hybrid cloud platform. Achieve better business performance.
What do you like best about the product?
Cloud Pak can use AWS services and features. Cloud-native development solution. Provide a secure way of cloud. Security. Hybrid cloud. Helps with data preparation for artificial intelligence. Collect, organize and analyze data, irrespective of where that data actually resides.
What do you dislike about the product?
Not that famous in the industry yet. Not very user-friendly. Multi-user login can be granted. Implementation is not that simple. Documentation and videos are limited.
What problems is the product solving and how is that benefiting you?
All-in-one hybrid cloud platform. Business automation. Help to provide security for the cloud environment. Helps to get info about potential risks and respond faster to those threats.
Review for IBM Cloud Pak for Data
What do you like best about the product?
With the help of automation and embedded AI, it helps data to be easily identified thus a great boon to data-driven business
What do you dislike about the product?
Service issues like backup and restore and sometimes installation and backup issues make it a little tedious
What problems is the product solving and how is that benefiting you?
Creating connectors to link the data of the organization with IBM Cloud Pak for Data
Great tool for Enterprise level Data Insights and much more
What do you like best about the product?
A lot of great features are provided by IBM tools. And cloud Pak for Data in particular is again something that comes with a bundle of great data-centric features, which makes the life of a data team easier in several aspects.
Data virtualization has been very useful, along with the ability to integrate with several other tools, as and when required.
Also, containerization is very crucial in maximum projects these days, and IBM cloud pak beautifully delivers this feature as well and helps in creating a lesser error-prone environment for everyone and giving faster deliveries and insights.
Data virtualization has been very useful, along with the ability to integrate with several other tools, as and when required.
Also, containerization is very crucial in maximum projects these days, and IBM cloud pak beautifully delivers this feature as well and helps in creating a lesser error-prone environment for everyone and giving faster deliveries and insights.
What do you dislike about the product?
I feel it is a bit complex and pricey though, and hence not easily approachable to integrate into smaller firms.
From the complexity perspective, it is because it offers tonnes of amazing features, but it becomes equally difficult to get a hang of everything and understand each feature and takes some time to get used to. So, maybe more tutorials and all should be there for better understanding and making knowledge transfer smooth for everyone
From the complexity perspective, it is because it offers tonnes of amazing features, but it becomes equally difficult to get a hang of everything and understand each feature and takes some time to get used to. So, maybe more tutorials and all should be there for better understanding and making knowledge transfer smooth for everyone
What problems is the product solving and how is that benefiting you?
Needed a hybrid cloud solution as our project required pulling data from several sources like DB, flat files, APIs etc. After that of course it needed to be staged and prepared and transformed accordingly as per the requirements and had to be made for different kinds of data analytics and insights generation. Then it was loaded to different targets, again according to the sub-stream it belonged to and w.r.t the end user. So, there would be a different kind of end-users, looking at the different granularity of the data.
A good business solution proposal
What do you like best about the product?
The final interface of the system is excellent because users who are not IT experts quickly learn how to use the system.
The UX was well used in this product/system.
The UX was well used in this product/system.
What do you dislike about the product?
Often corporate solutions try to look simple, but corporate environments are not. The propaganda that you can quickly: build, test, approve and maintain an environment like this. It is not easy, much less fast, because the bureaucracy and financial costs of corporate environments are high. So implementing projects like this takes months, if not years.
What problems is the product solving and how is that benefiting you?
It shares the same problems as the competition, and it promises miraculously quick and efficient solutions. But the reality is not that they are projects with a high level of complexity to achieve the promised result in advertising.
Recommendations to others considering the product:
Like any other product in this segment, you're going to hate the implementation/deploy step. But after a lot of suffering to make the integrations with the other systems of the corporation. Ah, a good product.
Cp4D platform
What do you like best about the product?
One-stop shop for all Analytics needs from collecting to analyzing allowing users to have everything needed to achieve optimal performance without affecting the underlying sources.
What do you dislike about the product?
Need to have open shift skills (container technology), requires more of a culture shift. It’s good in the long run but harder for users newer to containerization
What problems is the product solving and how is that benefiting you?
Getting faster time to value by having everything needed for a proper ad hoc analysis. Then as we adopt ML & AI capabilities we have the tools necessary to create, test, deploy, and manage those models.
Recommendations to others considering the product:
Launching a new Analytics project, this is a one UI integrating all the tools needed on the backend for a fully governed and functional Analytics environment
A good framework for data analytics and more
What do you like best about the product?
Rich with many features like data virtualization, integrations with many tools, unique way of data processing, etc. Not only that CPD has integrations with many external tools it as it runs on kubernetes we can bring in any kind of process or tool into the cluster with some work.
Also IBM team supported very well throughout the process. They even let us use their sandbox for while until we get comfortable with the system.
Also IBM team supported very well throughout the process. They even let us use their sandbox for while until we get comfortable with the system.
What do you dislike about the product?
Cost of the tool is not that approachable for smaller companies. I guess just like other IBM tools even this comes with certain cost. Another important factor to consider is its complexity. As there are many feature it brings in more complexity to the tool. It will take some time/training to understand all the aspects of this tool.
What problems is the product solving and how is that benefiting you?
We are trying to solve media related data processing problem using CPD. It involved pulling data from various sources like S3, databases, SFTP, even file uploads. Once the data from different sources are available in the system it has to be cleansed, transformed and made available for analytics at its lowest granularity. From their it would go into different paths - aggregation of the data for visualization by business teams while some folks would be using the raw data fore deep analytics.
Recommendations to others considering the product:
Its a good tool with many features... if your team likes it and fits you requirement list + budget then I would recommend it.
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