IBM Data Science Pros and Cons

The best think of IBM cloud pak liked by me is its good interface. Review collected by and hosted on G2.com.

The name of the service are hard to remember. Review collected by and hosted on G2.com.

The IBM Cloud Pack software is known for its flexibility and scalability, allowing users to easily manage and deploy applications on the IBM Cloud platform. Additionally, it offers a wide range of tools and services that can help businesses and organizations optimize their operations and improve their performance. Review collected by and hosted on G2.com.

Some users have reported that the IBM Cloud Pack software can be complex and difficult to navigate, particularly for those who are not familiar with the IBM Cloud platform. Additionally, the software may not be well-suited for small businesses or individuals with limited technical expertise. Some users also find the pricing and subscription model to be somewhat inflexible. Overall, it may not be the best fit for every organization or user. Review collected by and hosted on G2.com.

- 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.

Easy to use features, allows for quick results Review collected by and hosted on G2.com.

Color scheme can make differentiation difficult Review collected by and hosted on G2.com.

The data modelling concept and graphical options of the Modeler is amazing. Loved how accurate the data models were, pattern recognition and clustering were representative of all the data points and helped me a lot in recognising some key conclusions for my project. Review collected by and hosted on G2.com.

Although the Modeler has vast graphical representation options to choose from, most of them are obsolete and I faced many limitations while manipulating key data points. Also the pricing can be reconsidered. Review collected by and hosted on G2.com.

Its user-friendly interface especially in the IBM Pak fro Data envirronment. Advanced statistical features addressing major needs in the analytics journey : from data preparation, analysis and graphical reporting. Review collected by and hosted on G2.com.

A pricing approach which makes the soution costly for projects involving many different users. 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.

To create app easily by using cloud shell. Review collected by and hosted on G2.com.

I did not think there is dislike thing recently. Review collected by and hosted on G2.com.

1)User-friendly graphical interface for data preparation, modeling, and deployment.

2)Large selection of data preparation and modeling nodes.

3)Supports multiple data sources and data types.

4)Good documentation and resources for support.

5)Integration with other IBM tools such as Watson Studio and Cognos Analytics. Review collected by and hosted on G2.com.

1)Limited support for open-source machine learning libraries.

2)Expensive licensing and maintenance costs.

3)Can be resource-intensive for large and complex data sets. 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.