IBM Cloud Pak for Data Reviews

The last project I worked on was for the World Bank. I was tasked with designing the architecture for an e-commerce system aimed at rural people in Mexico, enabling them to sell products. I handled all the requirements and design aspects. The main focus of the project was the implementation of artificial intelligence and effective data management. I proposed IBM Cloud Pak for Data and an update to the cloud platform. 

Unfortunately, the project was not successful in terms of booking the final customer, as the required products were quite expensive. However, I designed the entire structure and architecture. That was one of my most recent projects. Another ongoing project with Cloud Pak is working on sales proposals for various customers in Mexico. The adoption of Cloud Pak for Data in Mexico is relatively slow compared to Data Station and Information Server, which is faster.

The main focus is on projecting sales and managing product renewals in the stores. That's more or less what I'm currently involved with regarding Cloud Pak for Data.

Its data preparation capabilities are highly valuable. You need to ensure that the data is properly created and provided in the most reliable format, especially for accurate predictions. 

For instance, IBM offers numerous artificial intelligence algorithms that require the data to be in the correct form and with precise information. We need to ingest all the data into the artificial intelligence models. I believe this is one of the primary objectives of IBM Cloud Pak for Data.

There are several specific connectors that we need to use, such as the one for SAP or XML. These connectors are not fully integrated into Cloud Pak for Data. However, they are very useful in database and information services for many of the projects I've worked on. 

Right now, the product is trying to be more maturity in terms of connectors. That, I believe, is an area where Cloud Pak can improve. Obviously, they are constantly working on refining the product. We are currently on version 4.5, and I have good relationships with some people at IBM.

They are actively striving to iterate and release new versions of the product. They are also focusing on improving Information Server and Rapid Stage 5.

In future releases, it would be beneficial to have more advanced data curation features. Specifically, I'm referring to data analysis and the quality dimensions associated with it. In my experience, this aspect is not as mature in Cloud Pak for Data compared to Information Server or database information analyzer, as they have been working more extensively on these areas.

They have been more focused on developing and enhancing those specific aspects. However, based on my research and discussions with my peers at IBM, I believe these features will be included in Cloud Pak in the near future.

I have been using IBM Cloud Pak for Data for three years. The last version I worked with was 4.5.

I would rate the stability an eight out of ten. The solution have lot of issues right now.

I would rate the scalability of this solution a nine out of ten. 

The customer service and support are good. It is one of the main part of the solution.

It depends because the IT infrastructure for Cloud Pak for Data is in the cloud. The implementation process is different from traditional system deployments. So, I would say it depends. 

I come from many years of working with Data Station and Information Server, which follow a classic implementation approach. However, implementing Cloud Pak is somewhat different. The vision or the concept behind it needs to be approached differently.

It's quite expensive. Small companies cannot afford such a product. It's mainly targeted towards larger companies.

The pricing is very high. 

You need to have sufficient funds and experienced personnel because it is a highly technical solution. It's not something that can be easily implemented without proper knowledge and expertise. 

For management, I would suggest taking smaller steps and gradually adapting the product within the company. Starting with smaller projects rather than diving into a major implementation.

The solution has a lot of potential, so I would rate it a nine out of ten.

Since my team and I are in the POC phase, we are interested in the solution's ETL layer and the data stage component. Also, we are yet to evaluate certain external aspects of the solution.

The tool depends on the control plane, an OpenShift container platform utilized as an orchestration layer. However, for our organization, it is not a standard Kubernetes orchestration layer that we are currently using. So, we have communicated this issue to IBM and asked if it is feasible to adapt the solution to work on a Kubernetes platform that we support.

I am currently employed at a banking organization utilizing a range of IT products. One of our current solutions is the Informatica ETL server, which is implemented on-premises. As for the IBM Cloud Pak for Data, our team is currently in the POC phase. The goal of the POC is to ensure that the solution complies with our organization's IT standards. Based on the POC's success criteria, we will evaluate the solution further to determine if it aligns with our organization's model. We will integrate it into our banking services if deemed a suitable fit. My company has a partnership with IBM. Also, we are users of the solution.

I won't be able to comment now on the solution's stability. Considering the tools that IBM supports, that's the other tools and other stuff. I think it should be a more scalable product. If it is able to meet the needs of different organizations, then it can be a wonderful product.

Scalability-wise, I rate the solution a nine or ten out of ten. It is a scalable solution considering its containerization benefits.

I rate the solution's initial setup a seven out of ten.

In terms of deployment timeline, our organization is currently in the strategic planning phase before actual deployment. It will take us a quarter to finalize our plans. However, we aim to complete the POC within the quarter and identify the success criteria. This will help us determine if the solution is aligned with our organization's strategic standards and can be implemented accordingly within the bank.

My suggestion for those considering using IBM Cloud Pak for Data is to evaluate it based on their own organization's policies and standards. While the product may be technically sound, its fit within the organization's system is the key factor to consider. In our case, the solution has the potential to be beneficial due to its scalability and use of different NFA's, which align with our organization's IT success. Overall, I rate the product a nine out of ten.

What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data.

One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things.

Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back.

I just started working on IBM Cloud Pak for Data, so my experience with it is hardly two weeks.

Currently, IBM Cloud Pak for Data is stable. My company is testing the enterprise version, which is stable.

We haven't tried scaling IBM Cloud Pak for Data yet. We also haven't tested its configuration because we're still analyzing it. We have a vast configuration, and IBM Cloud Pak for Data is still in the POC phase.

We're running six nodes on a Hadoop cluster of around four hundred terabytes, and we're still trying to figure out IBM Cloud Pak for Data.

I haven't contacted the technical support team for IBM Cloud Pak for Data.

We're still learning IBM Cloud Pak for Data, and we're reaching out to the community where others have been helping us out, but in terms of initial setup, it's not as simple as other solutions, and it could be a bit tricky.

On a scale of one to five, my rating for the initial setup for IBM Cloud Pak for Data is a three.

I don't have the exact licensing cost for IBM Cloud Pak for Data, as my company is still finalizing requirements, including monthly, yearly, and three-year licensing fees. Still, on a scale of one to five, I'd rate it a three because, compared to other vendors, it's more complicated.

I'm an expert on IBM InfoSphere, but now, I'm working on IBM Cloud Pak for Data.

Approximately five thousand people use IBM Cloud Pak for Data within the company.

My advice to others looking into implementing IBM Cloud Pak for Data is that it's helpful if you want to do AI. IBM has a package, but it would also depend on the number of mappings you have for the transformations. Ninety percent can be easily migrated, and the remaining ten percent tends to be more complicated. Right now, my company has five hundred thousand mappings, so the remaining ten percent is a considerable number, fifty thousand. It depends on the number of mappings you have. If you have a minimal number of mappings, you can find an alternative solution versus IBM Cloud Pak for Data. If you have poor centralization in mappings or a lot of mappings, IBM Cloud Pak for Data is an excellent solution to try.

IBM Cloud Pak for Data is a good solution, so I'm rating it nine out of ten. It has more enhanced logging, cataloging, and other features, so as a solution, IBM Cloud Pak for Data is good.

My company is a customer of IBM Cloud Pak for Data.

We have used IBM Cloud Pak for Data for machine learning and data science use cases for various customers.

The most valuable features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models.

Microsoft Azure has services, and you can have them be involved between any downstream applications for receiving results.

There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement. 

The automated machine learning models can be created based on combining those two models on the IBM Cloud. This is an area that is needing improvement. 

AIOps learning is used to manage the different versions of models of the data using these same models that have been made. This needs to improve.

One large hurdle we face is the AI lifecycle, this is a feature I would like to see. IBM needs to simplify the installation process and the administration process, which should be more streamlined. There should be more focus on decoupling the individual solutions to allow customer flexibility. The customer might not have all of it, but now they can disable it. The lifecycle data provides an entire range starting from collection of data, organizing, analysis and improving it.

This happens in real life, where customers do not like to put all their eggs in the same basket. They need a diversified platform, so they may select IBM Cloud Pak for Data for the sorting processes, then for the machine learning, they can do it using Watson Machine Learning and Watson Studio, whereas maybe for the design innovation part, they may go for some other solution. This homogeneity, or the diversification, they should be able to achieve  All of their solutions should be made in a fashion that can be plug and play. The installation or the setup process should not be complex, and integration with other solutions should be available.  

I have been using IBM Cloud Pak for Data for approximately two years.

The initial setup was a little complex. It is not that user-friendly, and it needs quite a bit of expertise to install, the installation between various different vendors is even more difficult, such as deploying it on the IBM Cloud is relatively easier than having it installed in Amazon AWS or Microsoft Azure, or similar cloud service. This is an area where a lot of improvement is required. 

We have been working with IBM Cloud Pak for Data version 2.0. After two years there was 3.0, which was improved a lot. Many of the processes have been made simpler, but there is still some improvement needed. Now we are in version 4.0. 

IBM Cloud Pak for Data was not installed by us, it was installed by IBM.

IBM Cloud Pak for Data is a very useful tool because it has the entire gamut of tools. Starting from collecting the data from various sources using direct integration or through data virtualization and then organizing it into catalogs and applying their organization's policies or if they have other enforcement policies on top of that. We can build the model from that data because you can refine the data. There is a lot of AI inside this single solution, we could bring a lot of homogeneity into the organization. The data discovery process and the finding of the right set of data for the right problem will become much easier because it's a very good solution.

I rate IBM Cloud Pak for Data a seven out of ten.

The main problem that happens in machine learning projects is that people come in and then work on making the models, and then the model is deployed in production. However, I find that there is a bias in collecting the model, and the model has to be more advanced. The model which you have built, it's very much dependent on the data from which the model was built. 

Most of the solutions have features for this in the new version of the model, while they don't provide support for the version of the data or the parameters of the data on which the model was built. When a new person joins the organization, or if the engineer who has worked on it has left the organization, if a new person comes in, and they don't have that reference data on which the model was built then we have to start from scratch. This is an area where many of the solutions which are on the market don't have a solution. This is where IBM should focus more on providing a solution. It is a major area that not only IBM but other vendors, should start working on to provide a solution. I understand Microsoft is working on a solution for this, and they have a new concept that they are introducing which is called Machine Teaching. If there is only a partial resolution or solution for this problem to structure data, they have to focus more on bringing new, innovative solutions.

Though I cannot provide information on the use cases in detail, I can say that the solution is used for data governance and data quality.

In the solution, data quality and ETL tools are the two features I found to be the most valuable ones.

The solution's user experience is an area that has room for improvement.

I have been using IBM Cloud Pak for Data for the past five years. Also, I'm using the latest version of the solution.

Stability-wise, I would say that the solution is fine. I rate the solution's stability an eight out of ten.

It is a scalable solution, and we have had no issues with its scalability in our company. I rate the solution's scalability a nine out of ten. Also, currently, we do not have any plans in our company to increase the number of uses using the solution. However, the product is being used extensively in our company.

We have contacted the solution's technical support team, and our organization is happy with them since they were helpful. I rate the solution's technical support as an eight out of ten.

Positive

Previously, we were using a different solution. We then switched to IBM Cloud Pak for Data because of its capabilities and cost-efficiency.

During the solution's initial setup, if you understand what you are doing, the process will be okay for you. However, the solution has got a quite complex implementation and configuration process. The deployment process took about three months. Also, the deployment model is cloud-based.

For the deployment process, our company sought the help of an integration partner.

We have around eight or nine people for the deployment and maintenance of the solution.

The solution was implemented in-house with an integration partner's help.

With the solution, we could meet our ROI requirements in our company.

For the licensing of the solution, there is a yearly payment that needs to be made. Also, since it is expensive, cost-wise, I rate the solution an eight or nine out of ten. There is no need to pay additional charges above the standard license and fees for the solution.

I recommend IBM Cloud Pak for Data to others who want to use it. Additionally, I suggest that those who plan to use the solution should train their staff properly. The performance and integration of the solution are fine. Overall, I rate the solution probably a six or seven out of ten.

The general use cases are the creation of a data catalogue. The module is called Watson Knowledge Catalog, and the tool is responsible for data profiling, rough data, and quality improvement by business people. You can model the data there, connect the data models with the business processes and create data lineage processes.

The general use cases are the creation of a data catalogue. The module is called Watson Knowledge Catalog, and the tool is responsible for data profiling, rough data, and quality improvement by business people. You can model the data there, connect the data models with the business processes and create data lineage processes.

The solution could have more connectors. Sometimes the customers request additional things that are not implemented, like Data Catalog.

We have been using this solution for about six years, and it was previously called IIS. We deploy on cloud, but there is an on-premises version. We haven't used it because it is a complicated system.

It is a stable solution 

It is a scalable solution, and I rate the scalability a ten out of ten. You can add processors and scale for additional people and users. Three people in our organization use this solution, and we plan to increase usage.

I rate the technical support a nine out of ten.

Positive

The return on investment depends on how you use it. If you improve the data quality, all the processes of artificial intelligence and machine learning are correct. If you have processes based on dirty data, data with errors or incomplete data, such processes are incorrect. So using such platforms in prediction and transactional systems also improves all the processes. You don't get financial returns per se, but the return on investment is huge if you improve your data.

It's a subscription license, so you must buy a yearly one. In comparison to the competition, I think the price is fair. It is not low, but it's lower than Informatica and Precisely company platforms. So I think the price is relatively low for such functionality.

I rate the solution a nine out of ten and recommend it to others.

We are using IBM Cloud Pak for Data for the development of models, such as credit scoring, anti-money laundering, and fraud control cases.

The most valuable feature of IBM Cloud Pak for Data is the Modeler flows. The ability to develop models using a graphical approach and the capability to connect to various sources, as well as the data virtualization capabilities, allow me to easily access and utilize data that is dispersed across different sources.

The interface could improve because sometimes it becomes slow. Sometimes there is a delay between clicks when using the software, which can make the development process slow. It can take a few seconds to complete one action, and then a few more seconds to do the next one.

It would be helpful to be able to connect in an easier way to data lakes or to structures that are residing in other cloud providers.

I have been using IBM Cloud Pak for Data for approximately 

The solution is stable.

I rate the scalability of IBM Cloud Pak for Data a nine out of ten.

I rate the scalability of IBM Cloud Pak for Data an eight out of ten.

The support can be slow to respond.

I rate the support from IBM Cloud Pak for Data a seven out of ten.

Neutral

The initial setup of IBM Cloud Pak for Data is easy because you can ask for it to deploy, but connecting the data sources can be a bit cumbersome sometimes.

The setup process requires one or two people, one with modeling expertise and the other with technical knowledge. If we were using the on-premise version, it would require more resources and personnel.

I rate the initial setup of IBM Cloud Pak for Data an eight out of ten.

IBM Cloud Pak for Data is expensive. If we include the training time and the machine learning, it's expensive. The cost of the execution is more reasonable.

We only need one or two people for maintaining the solution. This is thanks to the fact that we are using the cloud version of IBM Cloud Pak for Data. If we were using the on-premise version, it would require more resources and personnel.

My advice is if you are using Cloud Pak for Data on-premise, a highly technical team with knowledge of OpenShift and Red Hat operations and infrastructure setup is necessary. However, using the cloud service or SaaS version is much simpler and doesn't require as much technical expertise, making it a more favorable option.

It is a convenient platform that offers a variety of tools and algorithms, is easy to deploy and set up, and has many capabilities and functions that can be used in different projects. Additionally, it requires minimal coding compared to other vendor tools that I have used.

I rate IBM Cloud Pak for Data a nine out of ten.

I mainly use Cloud Pak in the FinTech and banking sectors.

Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF.

Cloud Pak would be improved with integration with cloud service providers like Cloudera.

I've been working with Cloud Pak for four years.

Cloud Pak is 100% stable.

Cloud Pak uses cloud infrastructure, so it's easy to scale up and expand the services.

As partners, we get the best technical support because we get direct contact. Sometimes the tickets take a long time to get resolved, but in urgent cases, we get the response we expect.

The initial setup was a little complex as building the cloud infrastructure to work on-prem wasn't easy, so the culture for the confirmation from monolithic solution to microservices and cloud-enabled services wasn't easy to convince the customer with. The deployment took around two to three months.

Cloud Pak's cost is a little high.

I would 100% recommend Cloud Pak and would rate it eight out of ten.