9.2Industry

Data & Analytics

Platforms and services enabling data collection, storage, analytics, artificial intelligence, and machine learning across enterprises.

8
Segments
32
Verticals

Overview

Data & Analytics covers the platforms and technologies for storing, processing, governing, analyzing, and deriving intelligence from data — the modern data stack (engineering, warehousing, BI), data science and machine learning, the explosive generative-AI and large-language-model wave, and the emerging quantum-computing frontier. It sits at the center of the AI revolution, as data infrastructure has become the foundation on which AI is built.

Demand is propelled by the exponential growth of data, the enterprise push to become data-driven, and above all the generative-AI gold rush. It is one of the largest and most heavily-invested technology categories — foundation-model developers (OpenAI, Anthropic, Google) are attracting unprecedented capital, and data-infrastructure platforms (Databricks, Snowflake) command enormous valuations. M&A and venture activity are intense across both AI and the underlying data stack.

Market snapshot

FragmentationConsolidating

Data and analytics span software publishing (NAICS 513210), data processing (518210), and IT services (541512) and are not separately disclosed as a category by the Census Bureau, so the segment is not separately sized here.

Business model & economics

Revenue model
Software/SaaS, consumption (compute/data), and API usage
Recurring revenue
High — recurring SaaS, consumption, and API revenue
EBITDA margin
Software-rich; foundation-model training capital-heavy
Capex intensity
Low
  • Data infrastructure is the foundation for AI.
  • Generative-AI gold rush attracting unprecedented capital.
  • Among the largest, most-invested tech categories.

M&A deal context

High deal activity

Who’s acquiring

Hyperscalers & data-platform majorsAI labs & strategicsVC- and PE-backed software investors

What’s driving deals

  • Generative-AI and data-infrastructure investment.
  • Modern-data-stack consolidation.
  • AI-driven analytics demand.

Segment classifications

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