Dataiku Customer Reviews 2025 | SoftwareReviews

Dataiku

Composite Score

7.7 /10

CX Score

7.9 /10

28 Reviews Write a Review

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What is Dataiku?

Dataiku is the platform democratizing access to data and enabling enterprises to build their own path to AI in a human-centric way. With Dataiku, everyone can get involved in data and AI projects on a single platform for design and production that delivers use cases in days, not months. No matter where they sit, they work in a safe and governed way that helps manage risk and create trust to drive high-quality outputs and value for your business.

Company Details

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Awards & Recognition

Dataiku won the following awards in the Machine Learning Platforms category

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5 Top Rated Capabilities

8 Top Rated Features

2024

2023 Emotional Footprint Champion

2023

Strategy and Innovation
Service Experience
Product Impact
Contract Negotiation
Conflict Resolution

2023

2023 Data Quadrant Gold Medalist

2023

4 Top Rated Capabilities

3 Top Rated Features

2023

2022 Emotional Footprint Champion

2022

Strategy and Innovation
Service Experience
Product Impact
Contract Negotiation
Conflict Resolution

2022

2022 Data Quadrant Gold Medalist

2022

4 Top Rated Capabilities

6 Top Rated Features

2022

Dataiku Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Dataiku.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

85 Likeliness to Recommend

97 Plan to Renew

1
Since last award

74 Satisfaction of Cost Relative to Value

1
Since last award

Product Experience

Negotiation and Contract

Conflict Resolution

Strategy & Innovation

Service Experience

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Emotional Footprint Overview

Product Experience:: 96%
Negotiation and Contract:: 91%
Conflict Resolution:: 98%
Strategy & Innovation:: 98%
Service Experience:: 97%

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+94 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love Dataiku?

0% Negative

3% Neutral

97% Positive

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Feature Ratings

Average 82

Data Pre-Processing

Openness and Flexibility

Data Exploration and Visualization

Ensembling

Feature Engineering

Data Ingestion

Algorithm Recommendation

Model Training

Model Tuning

Pre-Packaged AI/ML Services

Algorithm Diversity

Vendor Capability Ratings

Average 79

Vendor Support

Ease of Data Integration

Usability and Intuitiveness

Quality of Features

Breadth of Features

Business Value Created

Availability and Quality of Training

Ease of IT Administration

Ease of Implementation

Ease of Customization

Product Strategy and Rate of Improvement

Also Featured in...

Data Preparation for Analytics

Score 8.1

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Dataiku Reviews

Mansi A.

Role: Information Technology
Industry: Technology
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Oct 2024

Fantastic Product , Love the capabilities!

Likeliness to Recommend

9 /10

What differentiates Dataiku from other similar products?

Dataiku simplifies the management and readability of complex data pipelines by offering a range of built-in recipes that enable modular pipeline development. It stands out as one of the most effective tools for optimising your systems.

What is your favorite aspect of this product?

The product enables seamless collaboration among multiple users, allowing each to focus on their respective modules. Additionally, Dataiku DSS caters to both coders and non-coders, ensuring that the implementation of machine learning algorithms is accessible to all, not just those with coding expertise.

What do you dislike most about this product?

nothing, I don't dislike anything to be honest

What recommendations would you give to someone considering this product?

A end to end tool , its a full Jam Pack data science tool Definitely consider it!

Pros

Helps Innovate
Continually Improving Product
Performance Enhancing
Trustworthy

Sehaj K.

Role: Information Technology
Industry: Engineering
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Mar 2024

Fantastic and Fabulous

Likeliness to Recommend

9 /10

What differentiates Dataiku from other similar products?

Dataiku stands out for its user-friendly interface, comprehensive support for the end-to-end data science workflow, and its ability to scale from small teams to large enterprises while offering advanced features like machine learning automation and deployment capabilities.

What do you dislike most about this product?

I dont have any dislike

What recommendations would you give to someone considering this product?

I would recommend thoroughly evaluating your organization's data needs and objectives, conducting a trial to assess how well Dataiku aligns with those requirements, and leveraging available resources such as demos, documentation, and customer support to maximize its potential.

Pros

Continually Improving Product
Trustworthy
Efficient Service
Inspires Innovation

Sandip S.

Role: Information Technology
Industry: Technology
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted May 2023

Dataiku is a backbone of data industry

Likeliness to Recommend

8 /10

What differentiates Dataiku from other similar products?

Your large data pipelines are made more manageable and readable with Dataiku. There are many built-in recipes that can be used to help you make your pipeline modular. It is unquestionably among the best tools for your systems.

What is your favorite aspect of this product?

I can work with unstructured data, which has a variety of schema records, as well as structured data, which has a standard schema, thanks to Dataiku DSS. Given that it is comparable to our SQL tables and customised SQL queries, it helps with dataset manipulation on a unique level. When we perform transformations on our datasets, it supports data files that are present in our application servers and Hadoop clusters and provides DSS recipes. With the Pandas library, Pig scripts, and Hive queries included, it can also run our Python scripts.

What do you dislike most about this product?

You can't always accomplish your goals with the assistance of recipes. Because of this, the pipeline must be entirely programmed in, let's say, a Python recipe, which again reduces its modularity. Less documentation is also accessible.

What recommendations would you give to someone considering this product?

It is kind of needed tool for dataops and data transformation into various dimensions. It is the best tool for cleaning and transforming data in accordance with various business needs.

Pros

Helps Innovate
Continually Improving Product
Performance Enhancing
Trustworthy

Dataiku

What is Dataiku?

Company Details

Need Assistance?

Awards & Recognition

2023 Emotional Footprint Champion

2023 Data Quadrant Gold Medalist

2022 Emotional Footprint Champion

2022 Data Quadrant Gold Medalist

Dataiku Ratings

85 Likeliness to Recommend

97 Plan to Renew

1 Since last award

74 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

Emotional Footprint Overview

+94 Net Emotional Footprint

How much do users love Dataiku?

Chart

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Pre-Processing Ability to wrangle or pre-process data to ready it for model training.

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Ensembling 'Ability to combine ML models for best results.

Feature Engineering Ability to extract and build features from raw data.

Data Ingestion Ability to access data from various sources on-prem and in the cloud and of various type: structured, unstructured, and semi-structured, real-time, etc.

Algorithm Recommendation Ability to recommend a best ML algorithm to use based on dataset characteristics.

Model Training Ability to train a model with a range of data sets that you provide.

Model Tuning 'Ability to fine-tune models based on monitoring feedback within the platform.

Pre-Packaged AI/ML Services Pre-trained models and associated resources, e.g., for forecasting, recommendations, image and video analysis, NLP, voice, etc.

Algorithm Diversity Provides multiple diverse ready-to-use machine learning algorithms out-of-the-box.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Also Featured in...

Data Preparation for Analytics

Dataiku Reviews

Mansi A.

Fantastic Product , Love the capabilities!

Likeliness to Recommend

Pros

Sehaj K.

Fantastic and Fabulous

Likeliness to Recommend

Pros

Sandip S.

Dataiku is a backbone of data industry

Likeliness to Recommend

Pros

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1
Since last award

1
Since last award

Feature Ratings

Data Pre-Processing

Openness and Flexibility

Data Exploration and Visualization

Ensembling

Feature Engineering

Data Ingestion

Algorithm Recommendation

Model Training

Model Tuning

Pre-Packaged AI/ML Services

Algorithm Diversity

Vendor Capability Ratings

Vendor Support

Ease of Data Integration

Usability and Intuitiveness

Quality of Features

Breadth of Features

Business Value Created

Availability and Quality of Training

Ease of IT Administration

Ease of Implementation

Ease of Customization

Product Strategy and Rate of Improvement