- Connectivity: DSS plugins enable connecting to any data using R or Python for creating connectors. These connectors can be used for any file-based format for sharing.
- Data Exploration: Uses advanced code integrated with Jupyter to create custom reports and perform advanced analytical tasks.
- Data Preparation: Useful for scaling and to mark frequently used data; useful to modify code to suit requirements
- Machine Learning: Automatic selection of data to optimize model
- Model Deployment: Significant amounts of real-time predictions and elastic scaling is possible for traffic surges.
- Automation: Possible to deploy versioned models that are cleaned, enriched, and preprocessed.
USP : Rapid assembling of predictive data that changes crude information into a business affecting service. This product has advantages for all types of users: analytics leaders, data scientists, IT professionals, and business analysts. It helps analytics leaders in terms of managing productivity, collaboration, coordination, and measuring team growth. Data scientists benefit in terms of automation, modelling, flexibility, and reproducibility. IT professionals gain advantages pertaining to scalability, code & integration, operationalization, and data governance; while business analysts obtain data access, preparation, exploration, and automated ML benefits.
|Product Quality and Reliability|
|Product Features and Functionality|
|Breadth and Depth of Product Offering|
- Product Maturity / Data Management / Interactive Visualisati...Complicated UIData visualization offered by Dataiku is complicated. It does not offer drill-down functionality in visualizations or interactive charts that work together. Show More