DataRobot vs IBM Predictive Analytics comparison

"It's easy to do MLOps operations. It's a lot easier to manage jobs and see the logs if there's any drift in a model."

"DataRobot is highly automated, allowing data scientists to build models easily."

"We especially like the initial part of feature engineering, because feature engineering is included in most engines, but DataRobot has an excellent way of picking up the right features."

"DataRobot can be easy to use."

"By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month."

"The most valuable feature is the predictive capability in marketing use cases."

"The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum."

"There are some performance issues."

"If we could include our existing Python or R code in DataRobot, we could make it even better. The DataRobot that we have is specific to an industry, but most of the time we would have our own algorithms, which are specific to our own use case. If we had a way by which we could integrate our proprietary things into DataRobot with a simple integration, it would help us a lot."

"DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python. In this aspect, I see room for improvement in its functionality."

"Generative AI has taken pace, and I would like to see how DataRobot assists in doing generative AI and large language models."

"Using IBM Predictive Analytics requires more skill, resources, and training than some other solutions."

"The price of DataRobot is good because if you take the price of the solution which is approximately $65,000, it is less than a data scientist. There are very few data scientists available."

"We dropped the plan to use DataRobot, because we found the pricing to be on the higher sise. We liked DataRobot a lot, but due to the pricing, we dropped that idea."