IBM SPSS Modeler vs. Redash

Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.

Incentivized

Redash is well suited to situations where metrics are tracked on daily, weekly and monthly basis. Alerts can be set to emails which helps stakeholders to monitor performance on a frequent basis. It is less appropriate for cases where only dashboards are needed. Redash comes into picture where individuals can query and check data at the same time.

• Combine text and data
• Provide facilities for all phases of the data mining process.
• Use a node and stream paradigm to easily and quickly create models.

Incentivized

• Great Query Editor with Autocomplete feature
• Very easy to setup and quickly connect to variety of data sources
• Quick Dashboards with Simple UI which can be easily shareable

Incentivized

• Has very old style graphs, with lots of limitations.
• Some advanced statistical functions cannot be done through the menu.
• The data connectivity is not that extensive.
• It's an expensive tool.

Incentivized

• You need to have a good command over SQL to use Redash but if there could be some way where people can just pull data and do slice dice.
• It would be nice to have an excel kind of filters when all data is fetched.
• Some things like easy to customise the column names.

Incentivized

The online support board is helpful and the free add ons are incredibly appreciated.

Incentivized

When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.

Incentivized

I was not a part of the decision-making team who decided to go with Redash.

Incentivized

• Positive - Ease of decision making and reduction in product life cycle time.
• Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
• Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.

Incentivized

• Cost effective
• One tool for multiple purpose
• Easy access provision