IBM Data Science Experience (DSx) for big data analysis
April 05, 2018
IBM Data Science Experience (DSx) for big data analysis
Score 8 out of 10
Vetted Review
Verified User
Overall Satisfaction with IBM Data Science Experience (DSx)
We use IBM data science experience in order to create and train predictive analytics model: we implement some use cases about this topic, using different models. We've focused on model referring to vehicle registration using historical models and predictive variables like oil trend. Also, we use Jupyter Notebooks to analyze Twitter data and create data visualizations.
- You can use SPSS model in order to predict trend with historical data
- You can use R in order to clean up your data a Jupyter notebook
- You can use Jupyter Notebooks to analyze Twitter data and create data visualizations
- We try to install DSX in the local environment but it needs more resources
- I'd like a better visualization library for charts
- I'd like more webinar in order to introduce to the platform, also in Italian language
- I work with this product only for experimental works, I can't answer to this question.
- I hope that this product has the ability to proactively and repeatedly reduce costs and increase productivity.
- I suppose that this platform could improve decision making and customer service
IBM DSx is more comprehensive and easy to use, IBM Data science experience has many connectors to the data source and guarantees the portability with your old projects.