AdvancedMiner vs. JMP Pro

It can be time-consuming and expensive to visualize data in multi-cloud and on-premise applications. I would recommend my colleagues try this solution in order to collect, model, and visualize data automatically.

Incentivized

JMP Pro is perfectly suited for statistical analysis but users should have some statistical knowledge before using it since there may be some terms/functions in the software that are not widely used in other fields. No prior coding experience is needed to use JMP Pro. However, most people doing data processing would prefer to code their analysis.

Incentivized

• Different model integration, more so the external database analytical procedures.
• Further, AdvancedMiner helps in developing various statistical options and models, for advanced analysis.
• AdvancedMiner makes the extraction and the mining of data, a proper solution for wide range performance.

Incentivized

• Several types of segmentation models
• Conjoint design
• VERY user-friendly

Incentivized

• Nonetheless, AdvancedMiner [does] not focus on large enterprises' data visualization needs.

Incentivized

• JMP Pro is a really powerful tool for doing statistical analysis. Although the click environment does not require coding experience, new learners will still need to take a long time to know the parameters in the function before performing any analysis.
• The output from JMP Pro analysis (regression analysis) is not always easy to understand, especially when the parameters are programmed differently with the other similar software.

Incentivized

AdvancedMiner creates proper data extraction mechanisms, where storage procedures are also outlined and kept safe. Further, the statistical models are in proper work relationship with AdvancedMiner, which results in results that are accurate and authentic. Further, the complex database analysis from AdvancedMiner allows proper market evaluations and outstanding actionable insights.

Incentivized

It's much more user-friendly and has a wider statistical toolset.

Incentivized

• Self-service capabilities has enabled us to get rid of external data scientists.
• Workloads has reduced while saving time analyzing data automatically.
• We have increased time to value.

Incentivized

• It helped me put together meteorological data from different locations to show which area is the optimal location for wind energy.

Incentivized