Data quality - DataIQ

Enabling AI Agents to Find and Use the Right Context

How are organisations creating the data foundations that help AI agents access, understand and use information effectively?

Defining and Reporting Data Risk in Banking

As regulatory expectations increase, how do banks define, measure and communicate data risk in a way that drives ownership and action?

Operationalizing Data Retention

As data volumes continue to grow, how do organisations apply data retention consistently across systems and functions

Transferring Data and AI Solutions from Project Delivery into Business Ownership

Explore how organisations prepare business teams to own data and AI solutions and respond when adoption or value falls short.

Building the Processes to Govern Unstructured Data at Scale

Explore the business processes, governance foundations and practical approaches organisations are using to manage unstructured data securely and at scale.

Industry Pulse: The Rise of Decision Intelligence

Following the publication of our latest research on decision intelligence, this session explores what the findings signal for how organisations operate and how data and AI leaders deliver value.

Future-Proofing Your Test-and-Learn Capabilities In B2C

Discover how leading organisations are building test-and-learn capabilities to foster experimentation, improve customer engagement and deliver measurable business outcomes.

Making Data Governance and Data Quality a Shared Responsibility in Federated R&D Organisations

Exploring how federated organisations can drive accountability for data quality, align standards across teams, and build trusted data foundations for future AI and business needs.

Creating Organisational Impact with Data and AI

Data and AI are now key to value creation. The challenge is scaling impact, not capability. This event shows how leaders are embedding AI to build a repeatable, measurable AI-First future.

Automating AI Governance: Scaling Oversight Without Slowing Adoption

Explore how to automate and scale AI governance so it enables business innovation instead of slowing it down—sharing practical approaches to tooling, visibility, and continuous oversight.

Building and Validating a Scalable Data Quality Framework

Explore how to evolve an Azure data platform into a scalable, high-performance environment by structuring teams, processes, and operating models that drive continuous data and AI delivery.

The winners of the 2025 DataIQ Awards showcase the best of the data and AI industry

The 2025 DataIQ Awards have shone a spotlight on those making the difference in the data and AI industry, the pinnacle of leadership, and the emerging talent.

Scaling Azure-Based Data Platforms and Teams for Fast Flow Delivery

Explore how to evolve an Azure data platform into a scalable, high-performance environment by structuring teams, processes, and operating models that drive continuous data and AI delivery.

10 Tips to Successfully Migrate to Microsoft Fabric

Microsoft Fabric is gathering momentum across enterprise data teams, with leaders seeking best practices for migration. Those with experience are clear that migrating successfully isn’t just about technical setup but about designing new habits, ownership models and governance from day one.

Myth versus Reality of Technical Data Lineage

The path to robust data lineage is still uphill and strewn with pitfalls. DataIQ recently bought together leaders from mature organisations to exchange best practices on the topic, revealing a wealth common myths and practical advice on how to to meaningfully advance with technical data lineage.