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

FragmentationConsolidatingEstimate

Not sized here, and the reason is the insight: there is no data-and-analytics classification. The only code that touches it bundles web search portals with whatever else could not be placed, so a figure would report search advertising under an analytics heading. Read the segments below as line items inside a data platform budget rather than as separate markets — which is how the platform vendors are pricing them.

Business model & economics

Revenue model

Software/SaaS, consumption (compute/data), and API usage

Key economics

Recurring revenue
High

recurring SaaS, consumption, and API revenue

EBITDA margin
Software-rich; foundation-model training capital-heavy
Capex intensity
Low

Characteristics

  • 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

Deal activityHigh

Who’s acquiring

  • Hyperscalers & data-platform majors
  • AI labs & strategics
  • VC- and PE-backed software investors

What’s driving deals

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

Segments in this industry

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