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Dataiku

To systemize data use for exceptional business results by powering every company's ability to build its own extraordinary future.

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Dataiku SWOT Analysis

Updated: October 1, 2025 • 2025-Q4 Analysis

The Dataiku SWOT analysis reveals a company at a critical inflection point. Its established leadership in collaborative data science and strong enterprise footprint provide a powerful foundation. However, this is threatened by the pincer movement of Databricks' developer-focused platform and the low-cost convenience of hyperscalers. The primary battleground is now Generative AI; Dataiku must seize the narrative around enterprise governance for LLMs. The key priorities correctly identify the need to integrate GenAI, simplify the user and buying experience to accelerate adoption, and sharpen its competitive differentiation. Failure to act decisively on these fronts risks ceding its leadership position in the new AI-defined era. The path forward requires balancing deep enterprise features with radical simplicity.

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To systemize data use for exceptional business results by powering every company's ability to build its own extraordinary future.

Strengths

  • LEADERSHIP: Sustained Gartner MQ Leader status builds enterprise trust.
  • COLLABORATION: Unique platform bridges data scientists and business teams.
  • ECOSYSTEM: Deep partnerships with Snowflake, AWS, etc. drive adoption.
  • FLEXIBILITY: Support for visual flows and code appeals to broad user base.
  • CUSTOMERS: Blue-chip enterprise client base proves scalability and value.

Weaknesses

  • PRICING: High and complex pricing model is a key barrier to entry/growth.
  • PERCEPTION: Seen as less cutting-edge than Databricks by some developers.
  • ONBOARDING: Steep learning curve for advanced features slows adoption rate.
  • MARKETING: 'Everyday AI' message struggles to cut through GenAI noise.
  • PERFORMANCE: Can be outmatched by specialized tools on massive datasets.

Opportunities

  • GENERATIVE AI: Urgent enterprise need for LLM governance and deployment.
  • VERTICALS: Huge demand for tailored AI solutions in finance and retail.
  • MLOPS: Market focus on full lifecycle management makes our platform key.
  • DATA LITERACY: Non-technical employees need tools to use data safely.
  • CLOUD: Shift to cloud requires a neutral AI layer to avoid vendor lock-in.

Threats

  • COMPETITION: Databricks' unified Lakehouse platform is a major threat.
  • HYPERSCALERS: AWS, GCP, Azure offer integrated tools at a lower cost.
  • ECONOMY: Scrutiny on large software spends could lengthen sales cycles.
  • OPEN SOURCE: Maturing OSS tools (dbt, MLflow) can replace components.
  • TALENT: Fierce competition for top AI engineering and enterprise sellers.

Key Priorities

  • GENAI: Integrate and productize GenAI capabilities to lead the market.
  • ADOPTION: Simplify user experience and pricing to accelerate growth.
  • DIFFERENTIATE: Sharpen positioning against Databricks and hyperscalers.
  • ENTERPRISE: Deepen moat with advanced governance and vertical solutions.

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Strategic pillars derived from our vision-focused SWOT analysis

1

EVERYDAY AI

Democratize AI for business users, not just experts.

2

ENTERPRISE-GRADE

Win with governance, security, and scalability.

3

PLATFORM AGNOSTIC

Be the neutral layer across all clouds/data.

4

GENERATIVE AI HUB

Centralize GenAI development and governance.

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Dataiku Market

  • Founded: 2013
  • Market Share: Leader in Gartner Magic Quadrant for Data Science & ML Platforms
  • Customer Base: 450+ enterprise clients, including Forbes Global 2000 companies
  • Category:
    Data Science, ML Platform
  • SIC Code: 7372 Prepackaged Software
  • NAICS Code: 511210 InformationT
  • Location: New York, NY
  • Zip Code: 10010 New York, New York
    Congressional District: NY-12 NEW YORK
  • Employees: 1200
Competitors
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Databricks View Analysis
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Alteryx Request Analysis
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SAS Request Analysis
AWS (SageMaker) logo
AWS (SageMaker) Request Analysis
Google (Vertex AI) logo
Google (Vertex AI) Request Analysis
Products & Services
No products or services data available
Distribution Channels

Dataiku Product Market Fit Analysis

Updated: October 1, 2025

Dataiku provides the one simple platform for Everyday AI, systemizing data use to transform business. It empowers everyone—from analysts to data scientists—to create and deploy powerful AI applications, all while ensuring the enterprise-grade governance and trust that modern businesses require to scale responsibly and win in their markets. This is how extraordinary futures are built.

1

Systematize AI for scalable impact

2

Empower everyone with Everyday AI

3

Ensure trust with enterprise governance



Before State

  • Siloed data teams and chaotic toolchains
  • AI projects stuck in experimentation phase
  • Lack of governance and high model risk

After State

  • Unified platform for data collaboration
  • Systematized path from data to business AI
  • Full governance, trust, and transparency

Negative Impacts

  • Wasted resources and failed AI projects
  • Inability to scale AI across enterprise
  • Compliance and reputational risks

Positive Outcomes

  • Accelerated time-to-value for AI apps
  • Democratized data use for all employees
  • Scalable, responsible AI operations

Key Metrics

Customer Retention Rates
>95% for enterprise
Net Promoter Score (NPS)
Estimated 40-50
User Growth Rate
30%+ YoY user expansion within accounts
Customer Feedback/Reviews
180+ reviews on G2, avg 4.4 stars
Repeat Purchase Rates
High via subscription renewal model

Requirements

  • Centralized platform for diverse users
  • End-to-end MLOps and governance tools
  • Integration with existing data stacks

Why Dataiku

  • Deploying Dataiku as the core AI hub
  • Training both technical & business teams
  • Establishing a center of excellence

Dataiku Competitive Advantage

  • Persona-agnostic, collaborative design
  • Unmatched focus on enterprise governance
  • Open, neutral platform avoids lock-in

Proof Points

  • 150+ AI models in production at one bank
  • 90% reduction in manual reporting time
  • $10M cost savings via supply chain AI
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Dataiku Market Positioning

What You Do

  • Unified AI platform for design, deployment, and management of apps

Target Market

  • Enterprises, from data analysts to data scientists to business users

Differentiation

  • Collaborative interface for all personas
  • Strong governance and MLOps features
  • Platform and cloud agnostic

Revenue Streams

  • Annual software subscriptions
  • Professional services and training
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Dataiku Operations and Technology

Company Operations
  • Organizational Structure: Functional with geographic sales overlays
  • Supply Chain: Software-based; distributed via cloud and on-premise deployments
  • Tech Patents: Proprietary software for data analysis, ML, and AI governance
  • Website: https://www.dataiku.com/
Top Clients
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Dataiku Competitive Forces

Threat of New Entry

MODERATE: High barrier to entry to build a comparable enterprise-grade platform, but well-funded startups can target niche use cases.

Supplier Power

LOW: Key suppliers are cloud providers (AWS, GCP, Azure) and talent. Cloud is a competitive market, and talent is mobile.

Buyer Power

HIGH: Large enterprise customers have significant negotiating power, demand robust security, and often run competitive bake-offs.

Threat of Substitution

HIGH: 'Good enough' native tools from cloud providers, combinations of open-source libraries, and specialized point solutions can sub.

Competitive Rivalry

HIGH: Intense rivalry from Databricks, Alteryx, SAS, and cloud giants like AWS and Google, all competing for enterprise AI budgets.

AI Disclosure

This report was created using the Alignment Method—our proprietary process for guiding AI to reveal how it interprets your business and industry. These insights are for informational purposes only and do not constitute financial, legal, tax, or investment advice.

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Alignment LLC specializes in AI-powered business analysis. Through the Alignment Method, we combine advanced prompting, structured frameworks, and expert oversight to deliver actionable insights that help companies understand how AI sees their data and market position.