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Description
Cornerstone data analysis software enhances the efficiency of designing experiments and exploring data while allowing users to analyze dependencies and derive actionable insights immediately and interactively, all without requiring programming skills. It facilitates an engineer-friendly approach to executing statistical tasks, freeing users from the complexities of statistical intricacies. The software enables quick detection of correlations within data, even when operating within a Big Data framework. By employing statistically optimized experimental designs, it minimizes the number of experiments needed and accelerates the overall development process. Additionally, it supports rapid identification of usable process models and root-cause analysis through exploratory and visual data examination. Structured planning, efficient data collection, and thorough result analysis further optimize the experiments conducted. Users can easily investigate the impact of noise in process variables on the corresponding responses, and the software automatically captures compact, reusable workflows for future use, making it an invaluable tool for data-driven decision-making. Ultimately, Cornerstone empowers users to streamline their data analysis and experiment processes significantly.
Description
In a secure and manageable setting, users can swiftly derive insights from their data. Data can be collected in various formats and types, enabling the creation of new variables and the selection of specific cases of interest. Through effective data analysis techniques, both numerical and categorical variables can be thoroughly examined and analyzed. Results can be presented either in tabular form or through graphical representations. Additionally, users can investigate the relationships between different variables and assess the significance of these relationships. Various statistical tests, such as Pearson and Spearman correlations, Chi-Square tests, T-Tests for independent samples, Mann-Whitney, ANOVA, and Kruskal-Wallis, can be employed to achieve this. Moreover, the most commonly used measures of scale reliability can be easily selected and calculated. One can also verify the consistency of dimensions in the dataset. Utilizing measures like Cronbach's Alpha—both raw and standardized, with or without item deletion—Guttman’s six, and Intraclass correlation coefficients (ICC), provides further insights into the reliability of the data. This comprehensive approach ensures a thorough understanding of the data's structure and relationships.
API Access
Has API
API Access
Has API
Integrations
Elfsight
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$29.90/month/user
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
camLine
Founded
1989
Country
Germany
Website
www.camline.com/products/cornerstone/
Vendor Details
Company Name
Quark Analytics
Founded
2019
Country
Portugal
Website
www.quarkanalytics.com
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
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
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
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