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What is Palantir Gotham?

Integrating, managing, securing, and analyzing all organizational data is essential for modern enterprises. Data represents a crucial asset for businesses, and its sheer volume is staggering. It encompasses both structured formats, like log files, spreadsheets, tables, and charts, as well as unstructured forms, including emails, documents, images, videos, and more. Often, this data is stored across various disconnected systems, leading to a proliferation of types and an escalating volume that complicates its usability over time. Users reliant on this data do not categorize their needs into rows, columns, or mere text; instead, they focus on their organization's objectives and the challenges they encounter. They seek the ability to pose questions about their data and receive insights in a context that resonates with them. The Palantir Gotham Platform offers a robust solution to this problem. By integrating and transforming diverse types of data into a unified asset, Palantir Gotham enhances and categorizes information into clearly defined entities, including objects, individuals, locations, and events, thereby facilitating more informed decision-making. Ultimately, this platform empowers organizations to navigate their data landscape more effectively.

What is Affect-Tag RX?

Assessing emotions can yield critical insights for objective evaluations. By integrating cognitive data into your consumer and user research, you can make decisions that are based on genuine emotional reactions. The Affect-tag RX solution provides reliable and insightful emotional metrics through a secure web service and a customized dashboard. These metrics are obtained from physiological information collected via the Affect-tag RX mobile application and its unique smartband. This tool is designed for efficient data collection, fitting effortlessly into a variety of research methodologies. Participants can fully engage in their experiences without any potential biases interfering with the outcomes. Furthermore, our unique algorithms analyze physiological data in just a few minutes, granting researchers quick access to impactful insights. This rapid processing empowers researchers to respond promptly to the emotional data gathered, thereby enriching the overall research process and fostering a deeper understanding of consumer behavior. Ultimately, leveraging such technology not only streamlines research but also enhances the quality of insights derived from emotional analyses.

Media

Media

Integrations Supported

Palantir Apollo
Palantir Foundry

Integrations Supported

Palantir Apollo
Palantir Foundry

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$1500 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Palantir Technologies

Date Founded

2003

Company Location

United States

Company Website

www.palantir.com/palantir-gotham/

Company Facts

Organization Name

Neotrope

Date Founded

2007

Company Location

France

Company Website

affect-tag.com

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

Categories and Features

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

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