List of Dataiku Data Science Studio (DSS) Customers
Dataiku
125 West 25th Street,
New York, 10001, NY,
United States
New York, 10001, NY,
United States
1 646-568-7477
Professional Services
1250
$350M
Since 2010, our global team of researchers has been studying Dataiku Data Science Studio (DSS) customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Dataiku Data Science Studio (DSS) for ML and Data Science Platforms from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Dataiku Data Science Studio (DSS) for ML and Data Science Platforms include: Aviva Insurance, a United Kingdom based Insurance organisation with 24364 employees and revenues of $40.87 billion, Dentsu International (previously Dentsu Aegis Network), a United Kingdom based Media organisation with 25000 employees and revenues of $3.00 billion, BGL BNP Paribas, a Luxembourg based Banking and Financial Services organisation with 2152 employees and revenues of $1.85 billion, OVHcloud, a France based Professional Services organisation with 3002 employees and revenues of $1.19 billion, Royal Automobile Association of South Australia, a Australia based Professional Services organisation with 1300 employees and revenues of $445.0 million and many others.
Contact us if you need a completed and verified list of companies using Dataiku Data Science Studio (DSS), including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the Machine Learning software purchases.
The Dataiku Data Science Studio (DSS) customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of Machine Learning software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Aviva Insurance | Insurance | 24364 | $40.9B | United Kingdom | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2022 | n/a |
In 2022, Aviva Insurance deployed Dataiku Data Science Studio (DSS) as its centralized workbench within the ML and Data Science Platforms category. The implementation anchored the Customer Data Science Team, a customer-first center of excellence, and connected to Aviva’s broader Quantum data science practice of more than 700 data and analytics professionals. The program emphasized close pairing with line-of-business teams to ensure models deliver commercial outcomes rather than operating in an isolated research silo.
Dataiku Data Science Studio was configured to support the full data pipeline for Aviva’s customer analytics work, including data ingestion, interactive data preparation, model development, and automated push-to-production workflows. The platform was adopted as the team’s single workbench to enable multi-language development and collaborative notebooks, which allowed data scientists to use a mix of tools without fragmenting work across point solutions. The Customer Data Science Team applied agile methodologies to accelerate exploratory R and Python development into reproducible pipelines within Dataiku.
Operationally the deployment integrated DSS with Aviva’s marketing delivery channels using Dataiku API capabilities to operationalize models, most notably ADA, Aviva’s personalization AI built on Dataiku. The platform was used across customer analytics and marketing orchestration workflows and supported side-by-side engagement with business subject matter experts to validate model outputs and ensure production readiness. The implementation focused on enterprise-scale collaboration features to replace ad hoc laptop-based work and inconsistent knowledge sharing.
Governance and process changes accompanied the tooling shift, with the team prioritizing push-to-production practices, shared project assets, and a consultative engagement model embedded into business teams. Aviva reports concrete efficiency outcomes, citing a fivefold increase in end-to-end project throughput for the Customer Data Science Team and examples where model development timelines moved from two weeks to two days. The deployment also produced cultural changes in reproducibility and collaboration, positioning Dataiku Data Science Studio as the central platform for Aviva’s ML and Data Science Platforms efforts.
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BGL BNP Paribas | Banking and Financial Services | 2152 | $1.8B | Luxembourg | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
In 2017, BGL BNP Paribas implemented Dataiku Data Science Studio, DSS, to democratize access to data and analytic workflows. The deployment used Dataiku Data Science Studio in the ML and Data Science Platforms category to expand visibility and operational control over an existing advanced fraud detection model.
The project assembled data analytics and business users from the fraud department, data scientists from BGL BNP Paribas' data lab, and Dataiku personnel to coauthor data projects and model workflows. In eight weeks the teams used Dataiku Data Science Studio to prototype a new fraud detection model, leveraging collaborative visual recipes, code notebooks, and model evaluation tooling to iterate rapidly. Enterprise level security and monitoring features in Dataiku Data Science Studio were applied to preserve data governance standards while enabling broader access.
The implementation centralized model development and project artifacts on the Dataiku platform, creating governed project spaces and role based access controls to separate analytic experimentation from controlled datasets. Operational coverage focused on the fraud department and cross functional business users across the company, aligning business driven hypothesis creation with data lab led model refinement.
Governance changes introduced formal model monitoring and auditability through Dataiku Data Science Studio capabilities, and the collaborative workflow reduced handoffs between business and data teams. The rapid eight week prototype and the resulting accurate model delivered clear business value while maintaining compliance with the bank's data governance requirements.
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COYOTE | Professional Services | 240 | $119M | France | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
In 2017, Coyote implemented Dataiku Data Science Studio (DSS) in the ML and Data Science Platforms category to automate detection and correction of speed limit data used in its embedded maps. Coyote’s IoT fleet and mobile apps generate billions of anonymized rows of speed and position telemetry, creating a high volume data input that quality teams needed to analyze for map accuracy. The two companies already enjoyed a long-term relationship, in 2015 Coyote deployed a churn project developed using Dataiku Data Science Studio which validated broader application of predictive analytics to Coyote’s core product development.
Using Dataiku Data Science Studio, Coyote implemented machine learning workflows to segment roads into sections and analyze driving patterns within each segment. The implementation included anomaly detection and predictive modeling capabilities that estimate the likely speed limit for a given road section. Data mining and visualization capabilities in the platform were adopted to surface anomalies and support iterative model refinement through collaborative project workspaces.
Operational coverage focused on product quality and map accuracy workflows within Coyote’s quality teams and product development organization, leveraging the high volume IoT-derived dataset as the primary data source. Workflows were engineered to process billions of rows of anonymized telemetry and produce section-level predictions that feed downstream correction pipelines and quality assessment processes.
The deployment reinforced a data driven decision model across the company, shifting decisions from standard analytics reports to model based evidence and automated correction outputs. Collaborative features in Dataiku Data Science Studio enabled employees with differing skill sets to participate in model development, review, and deployment, expanding data mining and visualization practices beyond central analytics teams. The implementation automated parts of the speed limit correction process and embedded governance checkpoints for quality validation before updates were applied to map feeds.
Explicit outcomes reported by Coyote include a 9% increase in speed limit reliability on analyzed datasets and automation of the speed limit correction process. The project also contributed to a global data driven spirit within the company and increased customer loyalty. Dataiku Data Science Studio served as the platform enabling machine learning driven quality assurance for embedded map speed limits.
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Dentsu International (previously Dentsu Aegis Network) | Media | 25000 | $3.0B | United Kingdom | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
In 2017, Dentsu International implemented Dataiku Data Science Studio (DSS) to industrialize customer segmentation workflows within the ML and Data Science Platforms stack used by its data department to support media buying and sales recommendations. The initiative addressed a bottleneck where ad hoc code and repeated query development slowed delivery of segmentation recommendations to sales teams across TV, digital, search and other media channels.
The implementation centered on reproducible workflows and a collaborative sandbox for rapid prototyping, with Dataiku Data Science Studio enabling the team to build reusable projects rather than starting from scratch for each prospect. Engineers and data scientists constructed code devoted pipelines that run Scala on Spark, and the platform was used for predictive machine learning to surface weak signals and common feature patterns for audience definition.
Dataiku DSS was integrated with the company data lake that consolidated multiple source feeds, and models and pipelines executed against the Spark compute layer to operationalize segmentation output. The team used attribute level signals such as browser type and IP derived mobility indicators to define highly specific audiences that respond differently to creative and channel mixes.
Operational governance shifted from one off scripts to versioned, shareable projects and repeatable pipeline templates, reducing the need to write separate SQL, Python or Spark queries for similar projects. This change created a standardized handoff between the data department and sales, enabling reuse of model artifacts and accelerating delivery cycles.
As a result, Dentsu International reported being four times faster at delivering segmentation recommendations to the sales team, while also increasing the granularity of audiences available for targeting. Dataiku Data Science Studio within the ML and Data Science Platforms category freed the data department to focus on strategic modeling and prototyping, which supported the sales function in closing more business.
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OVHcloud | Professional Services | 3002 | $1.2B | France | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
In 2017, OVHcloud implemented Dataiku Data Science Studio (DSS) as part of its advanced analytics and data science strategy. Dataiku Data Science Studio (DSS) was adopted as OVHcloud's ML and Data Science Platforms solution to support cross-functional teams working on analytics projects and production machine learning workflows.
The deployment emphasized category-aligned capabilities including data preparation, visual and code-first model building, model operationalization and automation, and collaborative project workspaces. OVHcloud teams leveraged these functional modules to prototype and productionize models, standardize pipelines, and accelerate repeatable analytics across business functions such as SEO and broader advanced analytics efforts. The platform served as a shared environment for experiment tracking, pipeline orchestration, and collaborative development.
Governance and rollout focused on company-wide adoption, with teams across the company leveraging the tool for all kinds of projects and OVHcloud adding more users and projects every day. A specifically cited outcome was a revolutionary SEO project powered by machine learning built on Dataiku Data Science Studio (DSS). The implementation established the application as a central operational instrument for OVHcloud's advanced analytics and data science work.
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Professional Services | 700 | $135M | France | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
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Manufacturing | 1000 | $185M | France | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 1300 | $445M | Australia | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2021 | n/a |
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Banking and Financial Services | 140 | $15M | France | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
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Professional Services | 80 | $10M | France | Dataiku | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | 2017 | n/a |
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Buyer Intent: Companies Evaluating Dataiku Data Science Studio (DSS)
ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating Dataiku Data Science Studio (DSS). Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating Dataiku Data Science Studio (DSS) for ML and Data Science Platforms include:
- CVS Health, a United States based Healthcare organization with 219000 Employees
- Bank West BnP Paribas, a France based Banking and Financial Services company with 178000 Employees
- BP, a United Kingdom based Oil, Gas and Chemicals organization with 100500 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated |
|---|---|---|---|---|---|---|
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CVS Health | Healthcare | 219000 | $372.8B | United States | 2026-03-25 |
| Bank West BnP Paribas | Banking and Financial Services | 178000 | $76.5B | France | 2026-03-13 | |
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BP | Oil, Gas and Chemicals | 100500 | $189.2B | United Kingdom | 2026-02-03 |
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Education | 22365 | $3.0B | United States | 2026-01-28 |
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Insurance | 15 | $2M | United States | 2025-12-20 |
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Banking and Financial Services | 20 | $2M | United States | 2025-12-12 |
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Education | 925 | $168M | Mexico | 2025-12-05 |
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Retail | 2100000 | $681.0B | United States | 2025-10-20 |
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Life Sciences | 81000 | $63.6B | United States | 2025-08-22 |
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Construction and Real Estate | 1000 | $274M | South Korea | 2024-11-21 |
FAQ - APPS RUN THE WORLD Dataiku Data Science Studio (DSS) Coverage
Dataiku Data Science Studio (DSS) is a ML and Data Science Platforms solution from Dataiku.
Companies worldwide use Dataiku Data Science Studio (DSS), from small firms to large enterprises across 21+ industries.
Organizations such as Aviva Insurance, Dentsu International (previously Dentsu Aegis Network), BGL BNP Paribas, OVHcloud and Royal Automobile Association of South Australia are recorded users of
Dataiku Data Science Studio (DSS) for ML and Data Science Platforms.
Companies using Dataiku Data Science Studio (DSS) are most concentrated in Insurance, Media and Banking and Financial Services, with adoption spanning over 21 industries.
Companies using Dataiku Data Science Studio (DSS) are most concentrated in United Kingdom, Luxembourg and France, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Dataiku Data Science Studio (DSS) across Americas, EMEA, and APAC.
Companies using Dataiku Data Science Studio (DSS) range from small businesses with 0-100 employees - 8.33%, to mid-sized firms with 101-1,000 employees - 50%, large organizations with 1,001-10,000 employees - 25%, and global enterprises with 10,000+ employees - 16.67%.
Customers of Dataiku Data Science Studio (DSS) include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified Dataiku Data Science Studio (DSS) customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of ML and Data Science Platforms.