News & perspectives

Ideas for a more intelligent data future.

Practical thinking from DataNovaQ on the systems, methods and responsible choices behind modern data and AI.

Featured publication

Published by AI for Good · ITU

AI for good starts with quality data

We are proud to share that a case study by DataNovaQ founder Oussama Elmerrahi has been published on the AI for Good platform of the International Telecommunication Union.

The article explores why trustworthy AI begins before model deployment—with accurate, complete, representative and well-governed data—and offers a practical data-quality playbook for organisations.

Oussama ElmerrahiFounder, DataNovaQ · Regional Lead, Paris Hub

Read the case study on AI for Good

Curated by DataNovaQ

Industry watch

Selected external reporting and perspectives shaping the conversation around data, AI and governance.

IT Brief Australia

Governance

5 Data & AI governance trends every CDO should be watching in 2026

Why accountability, upstream verification, shared ownership, lineage and continuous data quality are becoming central to AI governance.

Euronext · Reuters

AI infrastructure

ASML raises 2026 forecast, expands capacity on AI chip demand

A market signal showing how sustained AI demand is translating into higher forecasts and capacity investment across semiconductor infrastructure.

OpenAI

AI strategy

How to manage AI investments in the agentic era

Five practical steps for connecting AI usage and spend to outcome-level value, governance, scalable workflows and proven demand.

FinTech Global

Risk & compliance

The data quality dilemma in financial crime risk

How incomplete and inconsistent information can undermine risk assessments, control effectiveness, regulatory confidence and operational efficiency.

Research Live · MRS

Data quality

Industry data quality benchmarking shows high survey removal rates

New benchmarking highlights substantial survey-response removal rates and the continuing need for stronger quality controls in research data.

What we explore

Our editorial themes

Data foundations

Engineering reliable, governed data products that teams can trust and use.

  • Engineering
  • Governance

Applied AI

Turning generative AI, RAG and automation into measurable business outcomes.

  • AI
  • Automation

Sustainable platforms

Building cloud and analytics systems with performance, cost and impact in balance.

  • Cloud
  • Sustainability

More perspectives

More stories are being prepared.

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