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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
DataMelt, or "DMelt", is an environment for numeric computations, data analysis, data mining and computational statistics. DataMelt allows you to plot functions and data in 2D or 3D, perform statistical testing, data mining, data analysis, numeric computations and function minimization. It also solves systems of linear and differential equations. There are also options for symbolic, non-linear, and linear regression. Java API integrates neural networks and data-manipulation techniques using various data-manipulation algorithms. Support is provided for elements of symbolic computations using Octave/Matlab programming.
DataMelt provides a Java platform-based computational environment. It can be used on different operating systems and programming languages. It is not limited to one programming language, unlike other statistical programs. This software combines Java, the most widely used enterprise language in the world, with the most popular data science scripting languages, Jython (Python), Groovy and JRuby.
API Access
Has API
API Access
Has API
Integrations
Apache NetBeans
Eclipse BIRT
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$0
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
jWork.ORG
Founded
2005
Country
United States
Website
datamelt.org
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
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
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