DSx for Consulting Assessment
Overall Satisfaction with IBM Data Science Experience (DSx)
As a senior consultant, I'm always looking to discover value in our's client data. This is crucial in our commercial model. Moreover, we always calculate the NPV of all the opportunities that we detect.I have been using DSx for anomalies detection in time series, understanding bias and variances and developing machine learning algorithms to estimate key dependent variables propensities.
Mainly, we have been helping retailers and their suppliers on stock optimization, price elasticity, and in-store stock shortage estimations.
Mainly, we have been helping retailers and their suppliers on stock optimization, price elasticity, and in-store stock shortage estimations.
- Very easy to use. Very intuitive.
- It's very easy to export the data architecture of a project and use it and modify it in a new project
- Having a very powerful cloud processing capability, allow to perform complex data analytics in any place with a good Internet connection
- At the beginning it's a little complex to understand some of the interface distribution
- Since the features are changing continuously, some of the tutorials don't fit the current version.
- Sometimes, the cloud platform run very slowly.
- Positive: Very low deployment cost
- Positive: ASP model, at the beginning it's cheaper than other solutions as on-premise. Hadoop is complex for almost everybody and expensive
- Negative: When a new solution is launched, weren't sure about the final cost for the client
Revolution R Enterprise
Dataiku DSS
Cloudera
Dataiku DSS
Cloudera