IBM Data Science Pros and Cons

It is well organized and supports a range of data science and ML tasks that can be performed almost seamlessly. Easy integration makes it easy to work on my existing data sets.

AI support through the available models is easy to deploy. Quite easy to use other the features as well.

Overall its a powerful tool for data. Review collected by and hosted on G2.com.

It might take some time to get familiar with the tool and all features as its quite extensive. Review collected by and hosted on G2.com.

A powerful AI/ML tool providing support for low code/no code AI development platform. Review collected by and hosted on G2.com.

High cost, high initial investment from partners and a steep learning curve. Review collected by and hosted on G2.com.

IBM Cloud Pak for Data has become an essential tool in driving our organization's digital transformation. The platform's comprehsnive integrated approach to data management, governance, analaytics, and AI has signifcantly streamlined our data operations and empowered us to make data-driven decisions with confidence. Review collected by and hosted on G2.com.

While the value proposition of IBM Cloud Pak for Data is undeniable, the initial setup and configuration can be complex and time-consuming, requiring dedicated resources and expertise. Review collected by and hosted on G2.com.

Unifying siloed data across our projects into a central platform has been fantastic. This capability has been invaluable, enabling us to consolidate disparate data sources, identify critical trends, and optimize resource allocation with percise. Review collected by and hosted on G2.com.

While IBM CP4D offers powerful integration and AI-driven insights, the inital setup complexisty can be daunting, requiring substantial IT expertise. Also, updates occasionally disrupt ongoing workflows, necessitating careful planning and testing to mitigate impacts. Review collected by and hosted on G2.com.

The platform to integerate multiple tools that ease the integeration and processing from end to end makes the high usage. easy to use and great support team. Review collected by and hosted on G2.com.

can reduse the cost of the service will improve the frequency of usage Review collected by and hosted on G2.com.

The best thing about IBM Watson Studios is its robust set of tools for data scientists and developers.

1. It seemlessly integrates & implements with a wide range of data sources making it easy to analyze the data.

2, It offers open source tools like Jupyter Notebooks and Tensor Flow which gives the flexibility to choose the right tool.

3. It has AI capabilities, which automates the process and makes it time efficient.

4. Customer Support is really great and versitile. One can have self guided documentations well as a paid support options.

5. It is very easy to use and it is frequently used considering the documentation and information provided. Review collected by and hosted on G2.com.

1. One of the disadvantage or the dislike for me is its cost, I find the cost is a bit on the higher side considering the market competetion.

2. It requires a specific & dedicated training and expertise to work on this tool.

3. It has dependency on IBM for ongoing support and updates. Review collected by and hosted on G2.com.

The best thing about IBM SPSS Modeler is that it is a really powerful statistical tool for data mining. I had to do a clustering for my market research work and spss had different clustering techniques inbuilt and easily deployable. Review collected by and hosted on G2.com.

The only thing l dislike about spss is that it is pretty difficult to be an expert in it since I was a beginner in this statistical tool and the flexibility is also very less. Review collected by and hosted on G2.com.

The comprehensive suite of capabilities within IBM Cloud Pak for Data is impressive. It brings together data management, governance, analytics, and AI tools in one integrated platform, fostering collaboration among data professionals. Its ability to streamline data workflows, ensure data governance, and empower users with AI-driven insights stands out as a powerful asset for businesses aiming to leverage their data effectively. Review collected by and hosted on G2.com.

challenges like the complexity of setup and configuration, potentially steep learning curves, and the need for significant customization to fit specific organizational needs. Additionally, there might be concerns about the cost associated with utilizing and maintaining the platform. Review collected by and hosted on G2.com.

I just really love the way how IBM Cp4D has a bunch of features in one tool.

It does data integration/data ingestion, data virtualization,data fabric,Building dashboards and dealing with ML aLgos etc.It's really flexible to use for data integration connecting to a different number of data sources . It's way advanced compared to the tools in market at the moment and very much user friendly . It's a game changer.I am a data engineer formerly worked with IBM where I got to use this amazing tool Review collected by and hosted on G2.com.

Nothing as such that we can dislike about IBM CP4D. Review collected by and hosted on G2.com.

The platform's UI is super intuitive, making it easy to create customizable dashboards for data analysis. It also provides a plethora of other useful features like data virtualization and containerization which helps in creating an error-free environment and improve the monitoring of the service by capturing insightful data. Review collected by and hosted on G2.com.

Nothing major that I can think of but there is definitely a bit of a learning curve which might make you hesitant to start with but the customer support is good. Review collected by and hosted on G2.com.