Alteryx, the all-in-one tool
February 14, 2025

Alteryx, the all-in-one tool

Anonymous | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Software Version

Designer Desktop

Overall Satisfaction with Alteryx Platform

we use Alteryx as an ETL in early stage data science product. The main product use case of this is to automate or Excel file transformations easily as well as to run data science functions like time, analysis, and regression in smaller models before building proper models for them. The scope is still limited for it, and it being used periodically by the team, but is highly useful for them.

Pros

  • ETL
  • Data Science
  • Modelling
  • Usability
  • Processing

Cons

  • More functions
  • More education
  • More Data science testing
  • Cheaper pricing
  • Reduced hours
  • Decreased churn
  • Higher delivery time
Alteryx is amazing for beginner data genius as well as people with the data engineering/for science background it makes their work flow is very easy to handle and processes much faster that they would do manually on top of it. It keeps everything consistent and make sure there are two errors in the file and all the data is delivered in a similar and uniform way, which might not be the case with someone is processing data Manual
Fivetran is a basic on its own, but it is very cloud based solution and useful for large teams handling large data sets, hence wasn’t useful for our case. That is why we picked Alteryx which provides easy to use and understand interface for low knowledge, people.

Do you think Alteryx Platform delivers good value for the price?

Not sure

Are you happy with Alteryx Platform's feature set?

Yes

Did Alteryx Platform live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Alteryx Platform go as expected?

Yes

Would you buy Alteryx Platform again?

Yes

Alteryx is well suited for smaller scale organisations or for large scale organisations where the team is not very technically advanced but are evolved at a lot of data processing, data, science, and data boarding workforce. It is not suited for high scale data as a lot of processing is done on your own PC, which might not be able to run billions of rows if you’re working with that large of data set.

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