Dataiku Customer Reviews 2024

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Dataiku

Composite Score

7.7 /10

CX Score

7.9 /10

28 Reviews Write a Review

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

Latest Award, 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

2
Since last award

96 Plan to Renew

1
Since last award

73 Satisfaction of Cost Relative to Value

3
Since last award

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Emotional Footprint Overview

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

Pre-Packaged AI/ML Services

Model Tuning

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 Customization

Ease of Implementation

Product Strategy and Rate of Improvement

Also Featured in...

Data Preparation for Analytics

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Dataiku Reviews

Vivek S.

Role: Consultant
Industry: Banking
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Apr 2022

Dataiku DSS - One-Stop for ML Needs

Likeliness to Recommend

10 /10

What differentiates Dataiku from other similar products?

Dataiku DSS integrates well with multiple data sources such as RDBMS databases, Amazon S3, etc. It allows users to collaborate and keep track of user contributions in the project. Dataiku DSS sets default values of hyperparameters for initial model training, which can be altered based on user needs. Overall, Dataiku DSS provides a single platform to implement end-to-end project deployment. Integration with RESTful APIs is a common example.

What is your favorite aspect of this product?

The product allows multiple user collaboration, and thus each user can individually focus on their respective modules. Secondly, Dataiku DSS can be used by coders and non-coders alike. Implementation of machine learning algorithms does not get limited to coders.

What do you dislike most about this product?

Dataiku DSS is a recently launched product, hence the customer support is still in it's early stages. Very limited blogs/support service websites are available at the moment.

What recommendations would you give to someone considering this product?

A go-to product. Definitely a one-stop tool for all machine learning and deployment applications.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Clément M.

Role: Operations
Industry: Retail
Involvement: Initial Implementation

Validated Review

Verified Reviewer

Submitted Apr 2022

Pefect to Accelerate & innovate on Data Science

Likeliness to Recommend

9 /10

What differentiates Dataiku from other similar products?

Ease the collaboration between Data expert, Both code & Visual features, always on improvement & enrichement

What is your favorite aspect of this product?

Visual features

What do you dislike most about this product?

the price :)

What recommendations would you give to someone considering this product?

perfect to accelerate time-to-market, you have to test it!

Pros

Continually Improving Product
Reliable
Performance Enhancing
Effective Service

Cons

Less Generous

Role: Information Technology
Industry: Food and Beverage
Involvement: End User of Application

Validated Review

Anonymous Reviewer

Submitted Apr 2022

Very effective in amplifying analyst capabilities.

Likeliness to Recommend

9 /10

Pros

Reliable
Performance Enhancing
Enables Productivity
Unique Features

How We Deliver

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

2 Since last award

96 Plan to Renew

1 Since last award

73 Satisfaction of Cost Relative to Value

3 Since last award

Emotional Footprint Overview

+94 Net Emotional Footprint

How much do users love Dataiku?

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.

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

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

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 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.

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.

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

Vivek S.

Dataiku DSS - One-Stop for ML Needs

Likeliness to Recommend

Pros

Clément M.

Pefect to Accelerate & innovate on Data Science

Likeliness to Recommend

Pros

Cons

Very effective in amplifying analyst capabilities.

Likeliness to Recommend

Pros

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Title

2
Since last award

1
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3
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Feature Ratings

Data Pre-Processing

Openness and Flexibility

Data Exploration and Visualization

Ensembling

Feature Engineering

Data Ingestion

Algorithm Recommendation

Model Training

Pre-Packaged AI/ML Services

Model Tuning

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 Customization

Ease of Implementation

Product Strategy and Rate of Improvement