Paxata vs. Tableau Prep

Paxata can be highly useful to someone who doesn't like/have any experience with writing codes to treat data before using it as input into BI dashboards. Paxata can accelerate data cleaning in environments where a large amount of unclean data is generated and business decisions on the go are required. It performs really well while dealing with natural language.

Incentivized

If your data sets are coming in without much stewardship then Tableau Prep can help to clean the data before you start trying to create visualizations for your end users. You will save a lot of time this way - rather than seeing problems once you are creating dashboards. If you don't have large data sets or your data is relatively simple, then Tableau Prep may not be needed.

Incentivized

• Visualize distributions in large data sets effectively which enable the user to quickly spot outliers and treat them appropriately
• Provides recommendation to merge datasets based on matching column values
• The cluster and edit feature in my opinion is its most powerful feature and reduces cardinality in column with text

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

• Doesn't provide recommendation on how to impute values
• There is a lag quite often
• We can say whether a column has errors or quality issues in the first look

Incentivized

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

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 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

Paxata is a much better tool when it comes to handling natural language but Talend provides recommendations on how to impute missing values and outliers. Paxata provides recommendations on dataset tie-ups and joins but Talend doesn't provide any such recommendations. In paxata you can visualize distribution of data in a column and filter them by dragging and selecting the section you'd like to retain

Incentivized

Before Prep, we had to do all the data joining and connecting in a Tableau Workbook. Not only did this cause workbooks connected with live data to run frustratingly slowly, a new connection and set-up had to be established every time a new workbook as created, even if you were working with the same data. The extracts produced by Prep allow several workbooks to be working from the same data set-up without any additional work, saving time and stress.

Incentivized

• It saves time to clean data
• It reduces the requirement of too many data engineer/stewards and hence adds positive impact on the return of the business

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