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Build cluster · Data, analytics, BI

Technology Rewired: Data and Analytics

Data and analytics moved from on-prem warehouses and desktop BI to cloud warehouses, ELT pipelines, and self-serve dashboards. AI added natural language queries. Agents now write SQL, build pipelines, and answer business questions directly, which makes trusted metric definitions and data quality the real bottleneck.

The shift: Questions get answered in plain English; analysts own definitions and trust.

Verified
2.3

Supervised agents today
3.2 in five years

How has the data and analytics team changed across five eras?

  1. Era 1 · On-prem

    Before 2005

    0.3

    Data lived in on-prem warehouses that a central BI team owned. Business users requested reports and waited weeks, and analysts spent most of their time in spreadsheets reconciling numbers.

  2. Era 2 · SaaS and cloud

    2005 to 2020

    1.0

    Cloud warehouses, ELT, and self-serve BI created analytics engineering and pushed dashboards to every team. Dashboard sprawl followed, with competing definitions of the same metric.

  3. Era 3 · AI-assisted

    2020 to 2024

    1.8

    Natural language query features and SQL copilots made analysts faster and let some business users ask simple questions. Answers were only as good as the underlying models and definitions.

  4. Era 4 · Agentic

    2024 onward

    2.3

    Agents now write and run SQL, build pipeline code, and answer ad hoc questions in chat with charts attached. The open problems are trust and access: which tables an agent may read, and whether its answer used the approved metric definition.

  5. Era 5 · Next 5 years

    2026 to 2031

    3.2

    My bet: the dashboard stops being the main interface, and data teams spend their time on semantic layers, quality, and access policy rather than report building. Analysts become editors and auditors of agent answers.

Which data and analytics software is being rewired?

No deep dives yet. The first ones are in the queue below.

Coming next

  • BI and dashboards
  • Data warehouses
  • ETL and ELT
  • Data catalogs
  • Product analytics
  • Customer data platforms
  • Spreadsheets
  • Data quality

Also wired into this category: Customer Onboarding Email.