World Congress 2025 • Aug 20, 2025 • Session details

Data Governance in the Era of AI

Kateřina Ščavnická

Feeding 900TB of raw data into AI does not yield insights. It creates expensive hallucinations. Kiwi.com implemented strict data mesh governance to transform this noise into actionable AI.

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#1 about 4 min

Struggling with ungoverned data lakes and massive storage costs

How hoarding raw customer interaction data led to massive storage costs and fragile analytics pipelines.

#2 about 1 min

Failing to analyze raw data with conversational AI

Why feeding poorly documented datasets to generative tools produces hallucinations and incorrect analysis.

#3 about 3 min

Adopting data mesh ownership and aggregated data models

Applying a data mesh philosophy ensures producers take responsibility for their domain datasets.

#4 about 3 min

Defining internal standards for high-quality data products

Evaluating internal data against six standard criteria including business checks and security.

#5 about 3 min

Categorizing data tiers and establishing data contracts

Prioritizing critical business pipelines by categorizing assets and enforcing service-level agreements between teams.

#6 about 3 min

Driving mindset shifts for effective data governance

Overcoming cultural resistance to fix broken pipelines creates a streamlined single source of truth.

#7 about 3 min

Enhancing data validation and self-service analytics with AI

Deploying artificial intelligence for semantic repository checks, anomaly detection, and conversational queries.

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