dataTap vs. Paxata

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
dataTap
Score 0.0 out of 10
N/A
dataTap is a user friendly visual data management platform from Zensors. The dataTap Python library is the primary interface for using dataTap's data management tools. Users can create datasets, stream annotations, and analyze model performance all with one library. Zensors states with dataTap, users can: - Begin training instantly - Work with all major ML frameworks…N/A
Paxata
Score 7.0 out of 10
N/A
N/AN/A
Pricing
dataTapPaxata
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
dataTapPaxata
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
Additional Details
More Pricing Information
Community Pulse
dataTapPaxata
Best Alternatives
dataTapPaxata
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 9.4 out of 10
IBM SPSS Modeler
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Score 9.4 out of 10
Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
IBM InfoSphere Information Server
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Score 8.0 out of 10
Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
dataTapPaxata
Likelihood to Recommend
-
(0 ratings)
9.0
(1 ratings)
User Testimonials
dataTapPaxata
Likelihood to Recommend
Zensors Inc.
No answers on this topic
Paxata
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.
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Pros
Zensors Inc.
No answers on this topic
Paxata
  • 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
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Cons
Zensors Inc.
No answers on this topic
Paxata
  • 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
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Alternatives Considered
Zensors Inc.
No answers on this topic
Paxata
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
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Return on Investment
Zensors Inc.
No answers on this topic
Paxata
  • 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
Read full review
ScreenShots

dataTap Screenshots

Screenshot of Install the client library.

`pip install datatap`

Register at [app.datatap.dev](https://app.datatap.dev/). Then, go to `Settings > Api Keys` to find your personal API key.

`export DATATAP_API_KEY="XXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXX"`

To begin with, select a dataset from the dataTap repositoryScreenshot of Copy the starter code based on your library preferenceScreenshot of Paste the starter code and start training.

from datatap import Api

api = Api()
coco = api.get_default_database().get_repository("_/coco")
dataset = coco.get_dataset("latest")
print("COCO: ", dataset)