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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IBM's Cloud Pak for Data is among the best data and AI platforms on the market.
What do you like best about the product?
- 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.
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
IBM Cloud Pak for Data is a multifaceted solution that deals with many business challenges around data and AI. These use cases include, but are not limited to:
- Achieving Data Fabric thanks to Data Virtualization, Data Integration and Data Access services.
- Data Governance and Data Privacy thanks to Watson Knowledge Catalog, IBM Guardium and Truata Anonymization.
- Operationalizing and Infusing AI with services for no code (AutoAI), low code (SPSS Modeler, Decision Optimization) or pure coding using Notebooks with languages such as Python, Scala and Java.
- Delivering exceptional customer care through conversational AI with Watson Assistant, Watson Discovery, Watson Tone Analyzer, Watson Text-To-Speech and Speech-To-Text and many other services from the catalog.
- Achieving Data Fabric thanks to Data Virtualization, Data Integration and Data Access services.
- Data Governance and Data Privacy thanks to Watson Knowledge Catalog, IBM Guardium and Truata Anonymization.
- Operationalizing and Infusing AI with services for no code (AutoAI), low code (SPSS Modeler, Decision Optimization) or pure coding using Notebooks with languages such as Python, Scala and Java.
- Delivering exceptional customer care through conversational AI with Watson Assistant, Watson Discovery, Watson Tone Analyzer, Watson Text-To-Speech and Speech-To-Text and many other services from the catalog.
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What do you like best about the product?
It is high performance computing solution which used for common platform across the cloud.
What do you dislike about the product?
It doesn't allow to start with small infrastructure which is drawback of it.
What problems is the product solving and how is that benefiting you?
It helps us to providd on-prem cloud solution to our . It help to utilize the resources well.
Competing solution in AI powered cloud native solution
What do you like best about the product?
Scalability, Quick deployment, solution integration with public cloud.
What do you dislike about the product?
Local backup solution like snapshots for DB.
What problems is the product solving and how is that benefiting you?
Various customer have their operation running in a hybrid model and heterogeneous work models like my medical client are able to manage lesser work intensive but require AI-powered compute to IBM's solution
IBM Cloud Pak - Overall Experience
What do you like best about the product?
End to end cloud with smart solution and automation
What do you dislike about the product?
Lots of legacy code makes it difficult for finding the right solution
What problems is the product solving and how is that benefiting you?
Very powerful suite for building epm apps
Complications makes it hard in implementing the solution
Complications makes it hard in implementing the solution
Robust solution to build applications with a modular architecture, run consistent operations
What do you like best about the product?
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
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
What do you dislike about the product?
There should be policy enforcement and governance with quota restrictions with ease of life cycle management to install and upgrades of core services.
What problems is the product solving and how is that benefiting you?
Streamlines the building and deployment of cloud-native data and AI workloads
Allows deployment and use of AI with transparency
Allows deployment and use of AI with transparency
One stop solution for data management and data analytics
What do you like best about the product?
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.
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.
What do you dislike about the product?
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.
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.
What problems is the product solving and how is that benefiting you?
With IBM cloud pak we are creating automated workflows for data analytics. We integrate IBM cloud pak with ERP systems to collect the data and reduce the ETL processes as well as do the near real time analysis of the data. This is the most used tool within org for the business process automation. This collects the data from different sources including multiple clouds and store centrally.
IBM CLOUD PAK is best product in data
What do you like best about the product?
Platform build with data fabric architecture.
What do you dislike about the product?
Not yet, because we used and integrate it
What problems is the product solving and how is that benefiting you?
Improve productiity and reduce complexity
It was really good
What do you like best about the product?
Seamless integration of monolith to containerised solution.
What do you dislike about the product?
Nothing to specify as such things as per our view.
What problems is the product solving and how is that benefiting you?
It's the hybrid cloud and provides Automation and Al capabilities to speed up product deployments and monitoring the usage
Multi Integrated Cognitive Data Platform!
What do you like best about the product?
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.
Large-scale data management across multiple environments.
Integration of AI helps to enable data formation.
What do you dislike about the product?
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.
Enhance third-party integrations smoothly so we can quickly implement integration from external sources.
What problems is the product solving and how is that benefiting you?
Helps newbies to get started with AI and data management and integration on enterprise level.
It helps to eliminate the need for costly billing.
It is straightforward for us to work on those data.
The overall computational errors have been reduced, and containerization has become crucial.
It helps to eliminate the need for costly billing.
It is straightforward for us to work on those data.
The overall computational errors have been reduced, and containerization has become crucial.
Best-in-class data management combined with IBM's AI/ML functionalities
What do you like best about the product?
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!
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
I am a cloud engineer and I struggle with multi-cloud projects where the solution requires an analytics platform that is not supported across multiple cloud platforms. IBM Cloud Pak for Data resolves my conern.
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