IBM Data Science Pros and Cons

IBM SPSS Modeler is an impressive and comprehensive data analysis tool that caters to the needs of both novice and experienced data scientists. Its array of features and functionalities make it a powerful choice for those seeking to extract valuable insights from their data. While it's not without its limitations, its strengths far outweigh its weaknesses.

SPSS Modeler boasts an intuitive interface that is relatively easy to navigate, even for users with limited coding experience. This accessibility makes it a great option for users who want to delve into data analysis without getting bogged down by complex programming. Review collected by and hosted on G2.com.

While the interface is user-friendly, mastering some of the more advanced features can still be challenging. In-depth understanding of statistics and machine learning concepts is required to utilize the software to its full potential. Review collected by and hosted on G2.com.

What i like most is we get certification and also notebooks for practice Review collected by and hosted on G2.com.

There is nothing as such to dislike but course fees Review collected by and hosted on G2.com.

The IBM SPSS Modeler is a leading visual information science and AI arrangement. Exploit open source-based advancement, including R or Python. Enable information researchers of all abilities - automatic and visual. Exploit multi-cloud approach - on-prem, public or confidential clouds. Start little and scale to a big business-wide, represented method.

By taking professional IBM SPSS Modeler, we get access to the accompanying -

Information access and commodities without information size limits.

Programmed information prep, fighting, ETL.

30+ base AI calculations, auto-displaying.

R extensibility/Python prearranging R extensibility/Python prearranging.

R extensibility/Python prearranging. Review collected by and hosted on G2.com.

An estimating approach which makes the solution expensive for projects including various clients.

It's pre overwhelmingly utilised for measurements.

Restricted help for open-source AI libraries.

Costly permitting and upkeep costs.

It can be an asset concentrated for vast and complex informational indexes. Review collected by and hosted on G2.com.

The platform supports the entire data and AI lifecycle, from data ingestion and preparation to model development and deployment. This end-to-end capability can enhance collaboration among data scientists, data engineers, and business analysts. Review collected by and hosted on G2.com.

I found it a little complex as a new user, especially for those who are new to the system. The range of features and tools may require a learning curve, and some users may prefer a more straightforward user interface. Review collected by and hosted on G2.com.

1. Adequate learning resources and extensive documentation.

2. Supports various models and is easy to implement them.

3. Easy integration with other IBM tools like Watson

4. People with less exposure to coding can use it efficiently. Review collected by and hosted on G2.com.

1. Complicated GUI, improvements are required in this aspect.

2. A bit pricey when it comes to multiple teams.

3. Limited integration with other languages like Java or Python Review collected by and hosted on G2.com.

IBM Watson Studio is an easy to deploy solution for ML processes and AI model developments in the cloud. The integration with the existing APIs and flexibility to deployment of instances in various environments are the best feature of IBM Watson Studio. Review collected by and hosted on G2.com.

It takes a longer time and a bit difficult process to integrate and train the ML models to meet the personalized requirements. Review collected by and hosted on G2.com.

It is faster and can load a lot of data without putting much load on the servers. The data is secured. Review collected by and hosted on G2.com.

The UI of it is very difficult to navigate. Even the documentation is not easy to follow or easily available. Review collected by and hosted on G2.com.

I like the most in IBM SPSS , they way is working to clean the data with the help of syntax and also use for data validation as well as for quick tabulation reports to reviw the while summary of the data. Review collected by and hosted on G2.com.

As of now there is now weak point but when the time of visualiztion of charting there is slightly behind from various tools to analyse the data in many various way according to the clients need. Review collected by and hosted on G2.com.

ability to switch between language models Review collected by and hosted on G2.com.

I don't like that except for Llama2, there are only small and rarely used language models Review collected by and hosted on G2.com.

The first time I introduced to Clementine Software in 2011 I was just fell in love with how easy it is. I really liked the detailed output of the analysis with everything one needs to interpret the result. The visual drag and drop feature where anyone can do any analysis with minimal coding. Review collected by and hosted on G2.com.

I really liked the spreadsheet feature but the UI was not that interesting. Review collected by and hosted on G2.com.