IBM Cloud Pak for Data (formerly IBM Cloud Private for Data) provides data management, data governance, and automated data discovery and classification.
This service works seamlessly and allows for secured connections with various data sources. It's efficient for parallel/distributed data processing and advanced data model building. It is pre-configured and has a very highly optimized data environment, which speaks for itself …
IBM has healing mechanisms when resource usage is high. This platform performs well, but when it runs out of capacity, it has crashed for many clients. This is innate in its original design.
This tool helps us with our data to generate meaningful insights that are really helpful in finding better business automation opportunities. It connects our data with multiple sources, govern it, find it, and use it for analysis. It also a source of collaboration from a …
The best thing about IBM Cloud it foster productivity by enabling users to find existing data or to request access to data. It provides modern tools that facilities analytics and remove silos, barriers to collaboration, thus enables users to spend less time finding data more …
Generally this tool has been very helpful and innovative because increase our workflow and collaboration using integrated multi-cloud platform. It also enables us to deploy in any flexible way like on-premises or cloud which saves time and hard disk space. It also enables us to …
This tool keeps on improving and I like the ability to manage both container and VM deployment, orchestration, upgrades, security, and compliance across hybrid resources in a consistent way and supports all major version of Kubernetes, like OpenShift, EKS, AKS, GKE and many …
better inbuilt integration with many system to store data
from multiple application to run matured AI/ML solution, which will give
prediction for utility service , SAP DI solution was not stable enough , faced
IBM Cloud Pak for Data takes the IBM Cognos solution and provides this on an enterprise cloud platform that can be extended to support better data integration and data science capabilities.