Dataiku - a complete Data Analytic and AI/ML solution
June 30, 2020

Dataiku - a complete Data Analytic and AI/ML solution

Anonymous | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source

Overall Satisfaction with Dataiku DSS

Dataiku is being used as the integrated data analytic/AI/ML platform. It is a corporate-level standard solution, across multiple regions and business domains. The data scientists use this platform to develop various data pipelines, and/or train the AI/ML models, verify the model performances and eventually deploy the model as service to benefit business critical IT applications (majorly serve the predictive analysis/automation and integration with RPA).
  • Very intuitive and easy to use UI, making a lot of types of users can collaborate with each other easily, by visualizing the same workflow.
  • Many building blocks can be reused immediately, avoid a lot of non-standard boiler plate implementation.
  • Data pre-analysis and feature engineering assistance increase the productivity as well as the efficiency of data scientists.
  • Many data connectors support wide range of data storage, from SQL, TeraData, Hadoop Hive, etc.
  • Support from research till final MaaS solution deployment.
  • The visualization feature of flow still has a lot room to improve, when the flow is complex.
  • The "non-coding" template/building block for deep learning lack of many important configurable parameters.
  • Lack of the unified way to allow applying the "design pattern" on the Python codes (if we want to develop our own module or building blocks.
  • Dataiku provides a consistent platform, covering almost all needs from the data analytic till AI/ML areas.
  • This platform "glues" all departments and business flows and IT data source together, making the data more exploitative.
Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.
The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.

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Chameleon, Cloudera DataFlow (formerly Hortonworks DataFlow), Sparx Systems Enterprise Architect
Dataiku is suitable for many steps of data processing pipeline development (from data collecting, filtering till cleaning, transformation and enhancement), and it is also good for the user who doesn't have too much in-depth AI/ML knowledge to quickly jump into it and give a try to solve some real-world problem.

Dataiku DSS Feature Ratings

Connect to Multiple Data Sources
Extend Existing Data Sources
Automatic Data Format Detection
MDM Integration
Interactive Data Analysis
Interactive Data Cleaning and Enrichment
Data Transformations
Data Encryption
Built-in Processors
Multiple Model Development Languages and Tools
Automated Machine Learning
Single platform for multiple model development
Self-Service Model Delivery
Flexible Model Publishing Options
Security, Governance, and Cost Controls