AdvancedMiner vs. Q Research Software

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

We use Q for quantitative data. If you know what you are doing it can still take a bit of time to manipulate your data into the most suitable format for the software to help you. But it is time well spent because once it's set up, Q makes the analysis a breeze. We use it for producing data tables, word clouds, significance testing, audience segmentation and coding of open-responses.

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

• Produces really easy to view tables
• Automatically applies significance testing to data, helping the user spot trends
• Create and insert your own variables and filters to help manipulate the data

Incentivized

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

Incentivized

• The pricing model is a little restrictive for smaller teams that only really need one license but have to buy a 2nd to help out modest users/users learning the ropes.
• Learning the basics can take quite a bit of time but they offer plenty of free resources that help you through it step-by-step
• Too be honest, I don't have too many complaints

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

We still use Excel in order to use Q, but all the analysis happens in Q. No need to learn formulas or reformat spreadsheets. Q does all the heavy lifting.

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

• Time saving - not exaggerating when I say we can do at least 10x the amount of analysis than we could without it
• More thorough insights obtained from our data sets
• Makes data engaging to other stakeholders

Incentivized