IBM Cloud Pak for Data Reviews

We are a consultancy company that specializes in data integration and we advise clients on what solutions will best meet their requirements.

The most valuable features are data virtualization and reporting. Data virtualization has to do with integrating data from different databases. 

The utilization of system resources is high.

The technical support could be a little better.

Having a "lite" version for a reduced price would be of interest to smaller companies.

I only began using the IBM Cloud Pak for Data recently, although some of the people in my team have been using it for close to a year and a half.

This product is stable enough. Like with all of these large packages, it's a combination of different tools that have been brought together, so stability is always an issue with them. It will improve over time.

IBM has enough experience with scalability, although I have found that the Cloud Pak for Data uses a lot of resources. It is not very resource-economic.

We get support directly from IBM and I would say that it's good enough. It can be better, but at this point, it's sufficient.

These integration-type products have a lot of things that are now pre-packaged in a cloud environment. There are similar solutions in Microsoft Azure, Google, and others. From an educational or teaching perspective, I think that as these systems start to have more influence in the market, there will be big a bigger concentration on them in terms of training.

At this point, I have only looked at them in a general sense and have not had much hands-on experience. I have focused more on open-source products.

I think that this solution is targetted for larger companies and it would be of interest to them, but for smaller companies, it would be tough to get value out of it.

I think that this product is too expensive for smaller companies.

I would rate this solution a five out of ten.

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.

One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance. 

One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios.

It's expected to grow, but we can't start with a large deployment. Usually, the customers go win another option, so we miss the opportunity to implement this platform.

We've been using Cloud Pak for Data for around a year.`

Cloud Pak is stable in my experience, but I don't typically operate it. I design the platform.

Setting up Cloud Pak is always complex. It requires a knowledge of containers and OpenShift. You also need to understand how to integrate the solution into your environment, or you can use it on a cloud, but it's not simple. It takes about one or two months if you are deploying a simple platform with only a few components.

I rate Cloud Pak for Data eight out of 10. It's an excellent tool that offers us many valuable features, but you have to understand how the solution will affect your operational model and rethink the way you deal with data. You're not only implementing a new tool but also an operational model.