| Target users | Business users, scientists and engineers | Data scientists and data engineers |
| Applications | Exploration, research and data discovery, business decision support | Programmatic automation and industrialization |
Deployment | ||
| Cloud – public and private | ||
| Local/user laptop | ||
| Server or HPC | ||
Data Input | ||
| Data Input Format | Excel, CSV, TXT | |
| Minimum Data Requirements | 30 rows | |
| Maximum File Size For Uploads | 40 MB | |
Data diagnostics | ||
| Input Data Visualization | Histogram and Box Plots | |
| Missing Data Resolution | Automatic | |
| Scaling | Automatic | |
| Balancing | Automatic | |
Modeling Settings and Processing | ||
| KPI data type supported | Regression, Classification | |
| Modeling Problems | Self-adjusting algorithm applied automatically | |
| Algorithm Selection | ||
| Outlier detection and elimination | ||
| Set modeling iterations | ||
| Extrapolation | ||
| Auto Data Compression | ||
Output | ||
| Linear Correlations | ||
| Non-linear relationships | ||
| Set correlation strength threshold for visualization of relationships | ||
| What-if scenarios | ||
| Individual Run Inspection | ||
| Model validation | ||
| Model export | C/C++, Excel, Matlab, Python or R | |
| DataStory export | PowerPoint or Matlab Toolbox | |
| Generate reports | ||
| Story Sharing | ||
| Integration | ||
| Deployment | ||
| Operationalization |
| Target users | Business users, scientists and engineers | Data scientists and data engineers |
| Applications | Exploration, research and data discovery, business decision support | Programmatic automation and industrialization |
Deployment | ||
| Cloud – public and private | ||
| Local/user laptop | ||
| Server or HPC | ||
Data Input | ||
| Data Input Format | Excel, CSV, TXT | |
| Minimum Data Requirements | 30 rows | |
| Maximum File Size For Uploads | 40 MB | |
Data diagnostics | ||
| Input Data Visualization | Histogram and Box Plots | |
| Missing Data Resolution | Automatic | |
| Scaling | Automatic | |
| Balancing | Automatic | |
Modeling Settings and Processing | ||
| KPI data type supported | Regression, Classification | |
| Modeling Problems | Self-adjusting algorithm applied automatically | |
| Algorithm Selection | ||
| Outlier detection and elimination | ||
| Set modeling iterations | ||
| Extrapolation | ||
| Auto Data Compression | ||
Output | ||
| Linear Correlations | ||
| Non-linear relationships | ||
| Set correlation strength threshold for visualization of relationships | ||
| What-if scenarios | ||
| Individual Run Inspection | ||
| Model validation | ||
| Model export | C/C++, Excel, Matlab, Python or R | |
| DataStory export | PowerPoint or Matlab Toolbox | |
| Generate reports | ||
| Story Sharing | ||
| Integration | ||
| Deployment | ||
| Operationalization |