IBM Cloud Pak for Data Reviews & Product Details - Page 3

- What is most helpful about IBM Cloud Pak for Data?

The platform's UI is very simple, intuitive and customizable making the overall user experience quite exceptional.

- What are the upsides of using IBM Cloud Pak for Data?

If you are a Chief Data Officer or a leader of Data and AI initiatives, then this platform is for you because it is built on the integration of several services designed to run wherever OpenShift is in place.

If your objective is to achieve Data Fabric while ensuring data privacy and compliance with regulations, then services such as Data Virtualization, Data Integration and Watson Knowledge Catalog are key to reaching such a goal. Review collected by and hosted on G2.com.

One of the big issues with the current release of Cloud Pak for Data (4.5.x) is the lack of connectors allowing business users and data citizens to connect to MANTA and leverage Business Data Lineage features. However, the product management of Cloud Pak for Data and Connectivity teams are working on delivering more connectors to allow for more integration with MANTA. Review collected by and hosted on G2.com.

The best feature would have to be the Watson Studio. Its a great tool to create more groups and to write code. It is very helpful for machine learning and data science use cases. Review collected by and hosted on G2.com.

The most difficult issue faced is the native features being decommissioned. When many changes are made like this it requires the team to come up with alternative ways to do things. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

Multi-cloud storage option with no limit to storing data.

Large-scale data management across multiple environments.

Integration of AI helps to enable data formation. Review collected by and hosted on G2.com.

It is a bit complex since its heavily loaded with so many features it will take time for the user to understand and implement solutions.

Enhance third-party integrations smoothly so we can quickly implement integration from external sources. Review collected by and hosted on G2.com.

Runs anywhere, connects security openly, installs easily in any environment—on a customer’s premises, private cloud, or public cloud

Connects all application data to self-service analytics that are integrated directly into the Cloud Paks platform

Simplifies development of cloud-native applications with open-source standards, common services, and integrated DevOps toolsets

Improves productivity by intelligently automating workflows and decisions (both routine and more complex)

Manages both container and VM deployment, orchestration, upgrades, security, and compliance across hybrid resources in a consistent way and supports all major flavors of Kubernetes, like OpenShift, EKS, AKS, IKS, GKE Review collected by and hosted on G2.com.

There should be policy enforcement and governance with quota restrictions with ease of life cycle management to install and upgrades of core services. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

A plethora of excellent features. It is beginner friendly and has an easy-to-use interface. The support provided across multiple cloud platforms is what makes it easily adaptable. The support provided for running Cloud Pak for Data on-premises while providing best-in-class security is an amazing add-on! Review collected by and hosted on G2.com.

The downside is that it requires a lot of infrastructure for initial deployment and isn't suitable for small-scale projects. Also, the pricing is too high for startups trying to understand the ecosystem. Review collected by and hosted on G2.com.

1. Catalog for AI services

2. Searching and indexing

3. Good for hybrid and multi cloud architectures

4. Data migration support.

5. Customer support is great.

5. Data virtualization and automation. Review collected by and hosted on G2.com.

1. UI could be better.

2. Learning curve in the beginning, since it is complex.

3. Pricing

4. Third-party integrations could be better

5. Should have more automated workflows. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.