Dataiku

Data Preparation

The Dataiku visual flow allows coders and non-coders alike to easily build data pipelines with datasets, recipes to join and transform datasets, and the ability to build predictive models.

The visual flow also has code and reusable plugin elements for customization and advanced functions.

Visualization

Dataiku saves time with quick visual analysis of columns, including the distribution of values, top values, outliers, invalids, and overall statistics.

For categorical data, the visual analysis includes the distribution by value, including the count and % of values for each value.

Machine Learning

To aid in the feature engineering process, Dataiku AutoML automatically fills missing values and converts non-numeric data into numerical values using well-established encoding techniques.

Users can also create new features using formulas, code, or built-in visual recipes to provide additional signals to improve model accuracy. Once created, Dataiku stores feature engineering steps in recipes for reuse in scoring and model retraining.

DataOps

Dataiku projects are the central place for all work and collaboration for users. Each Dataiku project has a visual flow, including the pipeline of datasets and recipes associated with the project.

Users can view the project and associated assets (like dashboards), check the project’s overall status, and view recent activity.

MLOps

The Dataiku unified deployer manages project files’ movement between Dataiku design nodes and production nodes for batch and real-time scoring. Project bundles package everything a project needs from the design environment to run on the production environment.

With Dataiku, data scientists can see all the deployed bundles, and data engineers of IT operations can quickly know when a new bundle requires testing and roll-out.

Analytic Apps

Dataiku makes it easy to create project dashboards and share them with business users. Scheduling updates for dashboards or triggering updates is easy and ensures the latest information is available.

With dashboards as part of a Dataiku project, business users and project stakeholders can easily see the outputs of AI projects and track KPIs and value.

Collaboration

Real advanced analytics projects require a series of steps that transform data from one state to the next, resulting in new datasets, features, metrics, charts, dashboards, predictive models, and applications.

The Dataiku visual flow is the canvas where teams collaborate on data projects. With the visual flow, everyone on the team can use common objects and visual language to describe the step-by-step approach and document the entire data process for future users.

Governance

Dataiku permissions control who on the team can access, read, and change a project. Permissions also include creating projects, executing code, executing applications, reading only content, and more. With Dataiku, users can belong to more than one group and have different permissions across projects, or organizations can have global permissions.

Explainability

Dataiku provides critical capabilities for explainable AI, including reports on feature importance, partial dependence plots, subpopulation analysis, and individual prediction explanations.

Together, these techniques can help explain how a model makes decisions and enable data scientists and key stakeholders to understand the factors influencing model predictions.

Architecture

Dataiku can run on-premise or in the cloud — with supported instances on Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure — integrating with storage and various computational layers for each cloud.

Plugins and Connectors

DSS plugins let you extend the power of DSS with your own datasets, recipes, and processors!

Visualization

AutoML

Build optimized models with minimal intervention (create a predictive model in just 3 clicks) with Dataiku’s powerful automated machine learning engine

Visual flow

Simplify collaboration and explainability of data workflows (no matter how big or complex) with Dataiku’s unique visual flow

Deployment

Put models in production with Dataiku’s built-in API Deployer, making high availability and scalable deployments easy.

Data connectors

Get instant access to any data source with 25+ native data connectors across cloud, on-premises databases, and enterprise applications.

Kubernetes

Spin up Kubernetes clusters (AKS, GKE, or EKS) from the Dataiku interface and scale up/down compute resources on-demand.

Deep Learning

Access deep learning capabilities (including training advanced neural networks in a few clicks!) in Dataiku’s visual machine learning environment.

Automation node

Separate development and production environments, plus easily deploy, update, and manage live projects.

Monitoring

Monitor the behavior and overall functional health of Dataiku to ensure production readiness and optimize resource allocation.

90+ data transformers

Scale transformation pipelines by running fully in-database (SQL) or in-cluster (Spark, Hadoop).

Cleanse, normalize, enrich

Cleanse, normalize, and enrich data with the visual Prepare Recipe.

Scenarios

Automate actions and workflows in Dataiku to leverage powerful scheduling capabilities.

Notebooks

Coders can feel at home with Dataiku’s native notebook environment for exploratory or experimental work.

Dashboards

Publish and share insights from data projects with other users and business stakeholders with custom dashboards.

Dataiku Applications

Empower more people within the organization to leverage AI and self-service analytics by visually designing and packaging data projects as reusable applications.

Spark

Dataiku lets you use a Spark engine to run visual recipes, execute code, train machine learning models, and more.

Pushdown execution

Optimize dataflow execution by pushing down Dataiku’s ETL and ML power to the database where the data lies.

Triggers

Automatically trigger scenarios in Dataiku, which can be configured based on time, dataset alterations, or any custom trigger.

Interactive statistics

Perform exploratory data analysis (EDA) in a dedicated visual interface built for advanced statisticians or anyone looking to uncover data patterns & relationships.

Charts

Pick from over 25 built-in chart formats or custom charts to share insights with others.

Version control

Version projects with Dataiku’s built-in, Git-based version control and get complete traceability of every action

Wikis

Track progress and collaborate on project goals and specifications by documenting relevant information

REST API

Interact with Dataiku from any external system — unlock AI insights and access admin controls from prefered applications.

Plugins

Choose from 100+ plugins in the Dataiku marketplace to go beyond built-in capabilities, supporting out-the-box solutions for a variety of use cases.

Time Series

Prepare and analyze time series data with Dataiku’s dedicated time series capabilities.

Processing engine

Leverage Dataiku’s flexible and highly scalable engine for optimal execution of Spark or in-database (SQL) jobs.

Python

Feel at home when working in Python with native integration and notebook-style coding environment.

Work natively in R with Dataiku’s deep integration, including a comprehensive R API.

Connection security

Secure connection to external systems with granular admin capabilities.

Environments

Create and work in standalone and self-contained environments to run Python or R code.

Metrics

Automatically measure indicators on elements of the workflow like datasets (e.g., size/shape), managed folders, and saved models (e.g., performance).