We performed a comparison between Google Cloud Datalab and IBM SPSS Modeler based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The infrastructure is highly reliable and efficient, contributing to a positive experience."
"Google Cloud Datalab is very customizable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The APIs are valuable."
"All of the features of this product are quite good."
"It is very scalable for non-technical people."
"We have been able to do some predictive modeling with it"
"We use analytics with the visual modeling capability to leverage productivity improvements."
"The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that."
"It scales. I have not run into any challenges where it will not perform."
"It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
"The interface should be more user-friendly."
"The product must be made more user-friendly."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"Customer support is hard to contact."
"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."
"The platform's cloud version needs improvements."
"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."
"The time series should be improved."
"Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization."
"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."
"The forecasting could be a bit easier."
Google Cloud Datalab is ranked 15th in Data Science Platforms with 5 reviews while IBM SPSS Modeler is ranked 12th in Data Science Platforms with 38 reviews. Google Cloud Datalab is rated 7.6, while IBM SPSS Modeler is rated 8.0. The top reviewer of Google Cloud Datalab writes "Easy to setup, stable and easy to design data pipelines". On the other hand, the top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". Google Cloud Datalab is most compared with Databricks, IBM SPSS Statistics, Cloudera Data Science Workbench, KNIME and Alteryx, whereas IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, IBM SPSS Statistics, RapidMiner and Alteryx. See our Google Cloud Datalab vs. IBM SPSS Modeler report.
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