Tableau Prep vs. Toad Data Point

Tableau Prep is a very powerful tool when it comes to creating workflows to monitor each stage for data analysis and quality issues. Also, it is convenient to explore the data with the wealth of operators and checking work at each stage of the process. Also, some areas that would help is if there are more types of automation provided.

Incentivized

Toad Data Point is the clear tool of choice if the end-user is interested in reports that are relatively simple to build using SQL code and export to Excel. It is less useful if the analyst also needs to run statistical models on the data and visualize the data for those functions I usually use RStudio or Jupyter Notebook which incorporates those features much more seamlessly.

Incentivized

• Display the raw data coming in from the data warehouse
• Point out situations that might be erroneous
• Show the distribution of raw data figures

Incentivized

• Ease of use. It is a very easy product to use without any particular training.
• Multiple data source connection. It easily connects to multiple data sources which allows you to use different data sources to run reports.
• Seamless application. Once you set everything up-- whether it is an FTP or export of data-- you can set it and forget it!

Incentivized

• Use of Macros within Workflow (and more types of automation)
• Join Editor also giving a SQL Update Query
• More types of visuals

Incentivized

• The program can error out when reconnecting to a database from a timeout but that is easily fixed by restarting the program.
• If you aren't familiar with database tools the UI can be overwhelming to some.

Incentivized

It is a valuable tool for generating and cleaning files for multiple purposes.

Incentivized

It works well and is user friendly for the basics but needs more options for bring in data (using SQL queries for example) and export format options.

Incentivized

I find Toad Data Point easy to use for both the novice and the experienced business analyst. If all you desire is to access data and create spreadsheets...this is a snap. Toad Data Point actually has cool data analysis features built into it. The newer workflow interface makes automating steps a snap

Incentivized

I have not really had to reach out for any kind of customer support for Tableau Prep, so I can't really say. However, the support that Tableau has given for their other products has been great, so I would assume it would be the same here. They are also constantly adding new features and providing software updates, and that is always a plus.

Incentivized

Live connections to cloud services (Google Sheets for example) and cloud hosted databases (cloud hosted SIS for example) for scheduled flows are not supported

Incentivized

Tableau Prep is covered in our license whereas Alteryx required additional fees and a separate license. Tableau Prep is similar to Tableau Desktop which a lot of our team is comfortable with so it wasn't difficult to get a feel for Tableau Prep. However, Alteryx would have been a totally new platform.

Incentivized

TOAD excels at connecting to divergent data sources, but appears geared more to DBAs than to regular query users. Microsoft's offerings excel against Microsoft SQL Server, but sometimes struggle with other data sources. However, SSMS and vs code excel at many developer productivity/workflow enhancements. vs code, in particular, has a lively extension system that allows it to be tailored for development/querying/model building/etc. That flexibility comes at a cost - the learning curve is steep for new users. The tradeoff between complexity and power may not be good for some environments/users/situations.

Incentivized

• Quicker data sets for online reports
• More efficient data cleaning Ad Hoc reports
• Costly if using data management to schedule data pull and cleaning (priced per viewer accounts not creator accounts)

Incentivized

• It is the least common denominator - not particularly optimized for our environment or workflows.
• Hangs or slowdowns add anywhere from 5% - 7% for projects utilizing large/complicated data setts. (This could be due to other IT-imposed constraints and not entirely due to TOAD.)
• Trying to perform some operations requires reading documentation and experimenting in order to figure out the TOAD-specific approaches and commands.
• It just works (when we understand it). Updates don't break things and things don't suddenly start behaving differently. Best of all, we don't mysteriously lose functionality.

Incentivized