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Description
Applying formulas to data without careful consideration often yields minimal benefits beyond the simplest scenarios. Data analysis in the real world involves a complex, multi-step approach, and Data Desk enhances this workflow by enabling the identification of potentially erroneous outliers through a single visual interface, while maintaining your selections as you navigate through various visualizations. This allows you to quickly recognize outliers and trends at a glance. By facilitating the rapid transformation of data into different formats, Data Desk promotes a culture of experimentation and creativity, leading to the development of more effective models. Users can interactively select and categorize data across multiple visualizations in real-time. With Data Desk's intuitive graphical interface, you can create plots and execute advanced analyses, and with just a click, you can export the R or Python code that replicates your work. Additionally, Data Desk ensures that your data is cleaned to meet R's standards, preventing issues with stray characters. Any comments added within your Data Desk environment seamlessly translate into comments in the generated code, enhancing the clarity and usability of your analyses. Such features not only streamline the analytical process but also foster a deeper understanding of the data at hand.
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
No details available.
Integrations
No details available.
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
Data Description
Website
datadescription.com
Vendor Details
Company Name
Quark Analytics
Founded
2019
Country
Portugal
Website
www.quarkanalytics.com
Product Features
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