Ratings and Reviews 1 Rating

Total
ease
features
design
support

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • TIMi Reviews & Ratings
    68 Ratings
    Company Website
  • Google Cloud BigQuery Reviews & Ratings
    2,017 Ratings
    Company Website
  • Teradata VantageCloud Reviews & Ratings
    1,122 Ratings
    Company Website
  • dbt Reviews & Ratings
    263 Ratings
    Company Website
  • SCIKIQ Reviews & Ratings
    14 Ratings
    Company Website
  • Harmoni Reviews & Ratings
    16 Ratings
    Company Website
  • DbVisualizer Reviews & Ratings
    583 Ratings
    Company Website
  • Fraud.net Reviews & Ratings
    56 Ratings
    Company Website
  • Grafana Cloud Reviews & Ratings
    853 Ratings
    Company Website
  • D&B Connect Reviews & Ratings
    188 Ratings
    Company Website

What is JMP Statistical Software?

JMP is a versatile data analysis application that works seamlessly on both Mac and Windows platforms, offering a blend of advanced statistical features and captivating interactive visualizations. Its intuitive drag-and-drop interface streamlines the data importation and analysis process, complemented by interconnected graphs, a vast array of sophisticated analytic tools, a built-in scripting language, and multiple sharing functionalities, all designed to enhance users' ability to examine their datasets both efficiently and effectively. Originally developed in the 1980s to capitalize on the advantages of graphical user interfaces in personal computing, JMP has continually progressed by integrating cutting-edge statistical methodologies and tailored analysis techniques from various sectors with each new iteration. Additionally, John Sall, the organization's founder, plays an active role as the Chief Architect, ensuring that the software evolves to meet the dynamic needs of analytical technology. This commitment to innovation and user experience underscores JMP's reputation as a leading choice for data analysis across numerous fields.

What is AWAI?

AWAI provides two innovative methods of operation, both utilizing the same analytical structure. The first method, known as group analysis, removes the requirement for a conventional fixed questionnaire; participants can instead formulate their questions in simple language and share an invite link, permitting respondents to engage without the necessity of creating an account. Each participant interacts with the AI on their own, which stimulates further dialogue to draw out richer insights. When the sessions conclude, the discussions are categorized based on opinions, the rationale behind them, and the frequency of each viewpoint, with distinctive opinions regarded as outliers instead of being averaged. This method can accommodate up to 100 users on a self-serve basis. The second approach features live meetings where participants can choose their desired language for communication and reading, with contributions organized by relevant topics as the conversation progresses. After the meeting, the content is arranged thematically rather than simply presented as a transcript. Both methods result in the production of a comprehensive document, where you can ask a straightforward query regarding the collected data, leading to a report that is exportable as a PDF and can be edited at no extra cost. Moreover, a public demo is available that does not require any registration, making it easy for prospective users to explore the functionalities of AWAI without any barriers. This effort highlights AWAI's commitment to accessibility and user engagement.

Media

Media

No images available

Integrations Supported

Amazon Aurora
Amazon Redshift
FACS
Firebird
Google Sheets
IBM Db2
IBM SPSS Statistics
Impala
MATLAB
Microsoft Excel
MySQL
OAuth
PostgreSQL
Python
R
SAP Adaptive Server Enterprise (ASE)
SAP HANA
SAS Visual Analytics
SAS Visual Data Science
Teradata QueryGrid

Integrations Supported

Amazon Aurora
Amazon Redshift
FACS
Firebird
Google Sheets
IBM Db2
IBM SPSS Statistics
Impala
MATLAB
Microsoft Excel
MySQL
OAuth
PostgreSQL
Python
R
SAP Adaptive Server Enterprise (ASE)
SAP HANA
SAS Visual Analytics
SAS Visual Data Science
Teradata QueryGrid

API Availability

Has API

API Availability

Has API

Pricing Information

$1320/year/user
$1320/year/user. Bulk discounts available.
Free Version
Free Trial Offered?

Pricing Information

$11.99/month
Free Version
Free Trial Offered?

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

JMP Statistical Discovery

Date Founded

1989

Company Location

United States

Company Website

www.jmp.com

Company Facts

Organization Name

OFFICE KAMIYA Inc.

Date Founded

2016

Company Location

Japan

Company Website

www.officekamiya.co.jp/

Categories and Features

Dashboard

Annotations
Data Source Integrations
Functions / Calculations
Interactive
KPIs
OLAP
Private Dashboards
Public Dashboards
Scorecards
Themes
Visual Analytics
Widgets

Data Analysis

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

Data Cleansing

Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

Data Mining

Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining

Data Preparation

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

Data Visualization

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

Predictive Analytics

AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis

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

Statistical Analysis

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization

Categories and Features

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

Popular Alternatives

Popular Alternatives

No Alternatives
Alchemite Reviews & Ratings

Alchemite

Intellegens
ndCurveMaster Reviews & Ratings

ndCurveMaster

SigmaLab Tomas Cepowski