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InetSoft Style Scope vs JungleWorks Kato comparison

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Buyer's Guide
Data Visualization
April 2024
Executive Summary

We performed a comparison between InetSoft Style Scope and JungleWorks Kato based on real PeerSpot user reviews.

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768,740 professionals have used our research since 2012.
Ranking
61st
out of 70 in Data Visualization
Views
29
Comparisons
22
Reviews
0
Average Words per Review
0
Rating
N/A
63rd
out of 70 in Data Visualization
Views
27
Comparisons
14
Reviews
0
Average Words per Review
0
Rating
N/A
Buyer's Guide
Data Visualization
April 2024
Download Free Report
Find out what your peers are saying about Tableau, Qlik, Splunk and others in Data Visualization. Updated: April 2024.
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768,740 professionals have used our research since 2012.
Comparisons
Also Known As
Kato
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InetSoft
JungleWorks
Overview

A Versatile, Responsive Web App that Adapts to All Devices Professional designers have full control on how their visual dashboards will behave on different devices.Even on small real estate devices like phones, visual dashboards still retain their full interactivity.

Make informed decisions quickly. Connect, model, and then explore your data with visual reports that you can collaborate, publish, and share. Kato integrates with other tools, so you can get up to speed quickly and work seamlessly with your existing solutions.

Sample Customers
WHO, IBM, MERCK, CHASE, FUJITSU, SIEMENS, VERIZON
Jugnoo, Juggernaut, Sylvan, Complete Express, JSW Steel, eHealth, LimeBike
Buyer's Guide
Data Visualization
April 2024
Download Free Report
Find out what your peers are saying about Tableau, Qlik, Splunk and others in Data Visualization. Updated: April 2024.
DOWNLOAD NOW
768,740 professionals have used our research since 2012.

InetSoft Style Scope is ranked 61st in Data Visualization while JungleWorks Kato is ranked 63rd in Data Visualization. InetSoft Style Scope is rated 0.0, while JungleWorks Kato is rated 0.0. On the other hand, InetSoft Style Scope is most compared with , whereas JungleWorks Kato is most compared with .

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We monitor all Data Visualization reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.