Case Study

From data silos to a strategic treasure trove

The introduction of a new data infrastructure reduces manual processes, which saves time and resources. Linking different data sources provides new insights into customer behavior and campaign performance, which leads to better decisions. Data access is simplified and legally secured.

Company

Mediaprint Zeitungs- und Zeitschriftenverlag GmbH & Co KG

Location

Vienna, Austria

Industry

Publishing

Details

Situation

In a preliminary project, among other things, challenges relating to the existing data landscape were identified and a new architecture was proposed
In addition, use cases for activating data potential were prioritized and specified
Many reports must be created with a great deal of manual effort and using workarounds

Complication

The existing data infrastructure no longer meets the requirements in terms of speed, scalability and accessibility
Independent modernization of the setup is not possible due to a lack of capacity and insufficient know-how in the area of modern data architectures
Wide range of data sources, complex data structures, demanding stakeholder alignment, strict antitrust and data protection regulations

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Solution

Introduction of a modern data stack based on BigQuery (data warehouse), Dataform (data modeling) and Airflow (scheduling)
Compliance with antitrust and data protection regulations by setting up three separate data warehouses and establishing appropriate governance
Implementation of three initial use cases: (1) editorial dashboard, (2) customer golden record and (3) advertising monetization dashboard

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Added value

Significant reduction of manual effort for evaluating the performance of editorial content and digital marketing channels
New analysis options by linking multiple data sources — especially online and offline sales information
Simplified, centralized and legally compliant access to data

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Image source: Fakurian on unsplash

Fundamental modernization of data infrastructure to strengthen MediaPrint's competitiveness

The complete MediaPrint transformation journey

This infrastructure implementation is Stage 3 the comprehensive MediaPrint transformation:

Phase 1: Strategic foundations → MediaPrint Data Strategy: Status quo Analysis and Roadmap Development

Phase 2: Organizational Change → People at the center of data strategy: Successful transformation at MediaPrint

Phase 3: Technical implementation 👈 This case study→ MediaPrint Infrastructure: Modern Data Stack Implementation

Outcome: From fragmented data silos to a strategic treasure trove

The company: MediaPrint as a pioneer in digitization

MediaPrint As Austria's largest newspaper publisher, combines well-known brands Kronen Zeitung and courier as well as other media formats. After the successful strategic realignment and organizational transformation, the company was ready for the final step: the technical modernization of the data infrastructure.

The implementation context

Based on the findings of Data Audits (phase 1) and the organizational realignment (phase 2) MediaPrint had clear priorities for technical implementation: architecture compliant with antitrust law, reduced manual effort and new analysis options through intelligent data linking.

The technical challenges: Legacy meets modern data stack

Challenge #1: Outdated data infrastructure

Die existing data infrastructure was met with the requirements relating to Speed, scalability, and accessibility Not fair anymore. Many reports had to be created with a great deal of manual effort and using workarounds.

Specific pain points:

Performance data The digital sector had to be laboriously linked to Excel tables
Daily manual reporting tied up significant resources
Deeper analyses were not technically possible

Challenge #2: Limited internal capacity

One independent modernization The setup was done lack of capacity and inadequate know-how not possible in the area of modern data architectures.

Challenge #3: Complex data landscape

Wide range of data sources, complex data structures, and demanding stakeholder alignment made integration significantly more difficult.

Challenge #4: Antitrust and data protection requirements

Strict antitrust and data protection regulations required a special architecture. MediaPrint operates with the brands Krone and Kurier in one Sensitive environment under antitrust law - Data processing had to be strictly regulated.

The solution: modern data stack with compliance-first architecture

Technical setup of the new data infrastructure

Core components of the Modern Data Stack:

BigQuery (Google Cloud): Scalable data warehouse solution
Dataform: Modern data modeling and transformation
Airflow: Workflow orchestration and scheduling
Antitrust law-compliant architecture: Three separate data warehouse instances

Architectural principles:

Compliance by Design: Antitrust and data protection requirements taken into account from the outset
Scalability: Infrastructure grows with business
Usability: Easy operation for various user groups
Agile implementation: Use-case-driven approach for quick results

Antitrust law-compliant architecture

Special challenge: Compliance with antitrust and data protection regulations

Innovative solution: Three separate data warehouse instances

Separate instance for each part of the organization (crown, courier, overarching)
Strict data separation between different newspaper brands
Controlled Aggregation: Only specific, aggregated information for comprehensive analyses
Clear access control: Prevents illegal access to data between parts of the organization

Strategic use case implementation

Use Case #1: Editorial Dashboard

Target: Comprehensive overview of digital content performance
Before: Cumbersome manual work steps, Excel-based links
After: Integrated data sources, automated insights, data-driven decisions
Impact: Analysts have more time for deeper questions

Use Case #2: Customer Golden Record

Target: Combining customer data from online and offline worlds
Before: Fragmented customer view, separate systems
After: 360° customer view across all touchpoints
Impact: Well-founded sales decisions, improved customer loyalty

Use Case #3: Advertising Monetization Dashboard

Target: Central overview of the performance of various advertising channels
Before: Manual campaign analysis, separate data sources
After: Integrated campaign performance and revenue analysis
Impact: Well-founded campaign management decisions with less effort

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The measurable results: Quantified business impact

Operational excellence improvements

Manual effort reduction:

Editorial reporting: From 4 hours a day to 30 minutes (87% reduction)
Customer Analytics: From 2 days a week to 2 hours (95% reduction)
Advertising Performance: From 3 hours a day to 45 minutes (75% reduction)

Data timeliness improvements:

Real-Time Content Performance: Now minute updates instead of daily
Customer Insights: Available from weekly to daily
Campaign Optimization: Adjustments are possible from monthly to real-time

System Performance:

Query Response Time: Complex analyses from 30+ minutes to less than 2 minutes
Data Processing: 10x faster data processing with BigQuery
Concurrent Users: 25 simultaneous analysts without loss of performance

Business impact metrics

Improved decision quality:

Content Strategy: Data-based editorial decisions in 90% of cases
Customer Targeting: 35% more precise target group targeting through Golden Record
Advertising Optimization: 28% better campaign performance through integrated analytics

Revenue Attribution:

Digital content: Clear performance metrics for all digital content for the first time
Cross-selling: Improved customer view enables 22% more cross-selling success
Advertising Yield: 15% higher efficiency in advertising campaign management

Technical excellence KPIs

Infrastructure stability:

System Uptime: 99.9% availability of the data platform
Data Quality: Automated quality checks with 94% success rate
Backup & recovery: Complete disaster recovery in under 2 hours

Scalability success:

Data Volume Growth: System processes 5x more data than legacy setup
User Adoption: 78% of all authorized users actively use the new platform
New Use Cases: 12 more use cases in the pipeline for rollout 2025

Compliance & Governance Excellence

Antitrust law compliance:

100% data separation guaranteed between organizational parts
Audit-ready: Complete documentation of all data flows for authorities
Legal Approval: Architecture validated by antitrust law experts

GDPR compliance:

Automated Data Subject Rights: Processing in less than 24 hours
Privacy by Design: All data flows implemented in compliance with GDPR
Consent Management: Granular consents across all systems

Lessons Learned: Success Factors for Media Infrastructure Transformation

What led to success

‍Agile, use-case-driven approach: The focus on specific business applications Instead of purely technical migration, it created immediate added value and stakeholder buy-in.‍
Compliance-first architecture: The early consideration Antitrust and data protection requirements prevented subsequent redesign efforts and legal problems.‍
Continuous transfer of knowledge: Close exchange With the internal data team, ensured sustainable independence in future development and operation.‍
Stakeholder integration: Cross-functional collaboration between IT, editorial, marketing and sales throughout the implementation.

Challenges overcome

Challenge: Complex antitrust requirements

Solution: Three separate data warehouse instances with controlled aggregation

‍Learning: Treat compliance requirements as an architectural design principle

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Challenge: Limited internal capacity for modern tools

‍Solution: Hands-on training and gradual transfer of knowledge

‍Learning: Change management is just as important as technical implementation

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Challenge: Stakeholder alignment in complex organizations

‍Solution: Use case-focused communication with measurable quick wins

‍Learning: Communicate business value, non-technical features

Industry relevance: Modern data stack for media companies

Universal media industry challenges

Antitrust restrictions: Like MediaPrint, many market-leading media companies are facing antitrust requirements. Die Three warehouse architecture is a transferable solution for similar situations.

Legacy system integration: Traditional media companies have established IT landscapes. The agile, use-case-driven approach minimizes disruption with maximum business impact.

Compliance complexity: Require GDPR, media law and antitrust regulations Compliance-by-design - no subsequent adjustments.

Transferable technology approaches

Tool stack by media house size:

Regional media houses (50-200MA):

Data warehouse: BigQuery default
transformation: Dataform or dbt core
Orchestration: Google Cloud Composer (managed Airflow)

Medium-sized media groups (200-1000 MA):

Data warehouse: BigQuery Enterprise
transformation: Dataform + dbt cloud
Orchestration: Enterprise Airflow Setup

Large media companies (1000+ MA):

Multi-cloud setup: BigQuery+Snowflake Hybrid
Enterprise Transformation: Custom dbt + dataform
Advanced Orchestration: Airflow + Kubernetes

Cultural change: From manual to data-driven

Transforming working methods

Editorial area:

Before: Intuitive content decisions, little performance feedback
After: Data-based editorial strategy, real-time content optimization
Cultural Shift: From “gut feeling” to “data-informed intuition”

Sales area:

Before: Fragmented customer view, reactive approach
After: 360° customer view, proactive cross-selling strategies
Cultural Shift: From “Product Push” to “Customer-Centric” Approach

Marketing/advertising:

Before: Campaign optimization based on monthly reports
After: Real-time campaign optimization, data-based budget allocation
Cultural Shift: From “Set-and-Forget” to “Continuous Optimization”

Organizational successes

Cross-departmental collaboration: The new data transparency improved Massive collaboration between departments. Common data basis created a common understanding of priorities and success metrics.

Data-driven decision-making culture: Data-based decision making was more firmly anchored in all relevant areas of the company — a cultural change that forms the basis for long-term digital competitiveness.

The project team: expertise for your success

Responsible for the project:

Thomas Borlik: Managing Partner, Strategic Lead
Mike Kamysz: Managing Partner, Technical Lead
Roxane Stelzel: Senior Data Consultant

The Reference contact can be arranged upon request - proof of successful project implementation and sustainable customer satisfaction.

Advanced media data strategies

The MediaPrint infrastructure transformation exemplifies how modern data architectures are advancing media companies technically and organizationally. Complement your understanding of the entire transformation:

The complete MediaPrint journey

Phase 1: MediaPrint Data Strategy - Develop Strategic Foundations
Phase 2: MediaPrint Transformation - Implementing Organizational Change Successfully
Phase 3: MediaPrint Infrastructure - Modern Data Stack Implementation (This case study)

Strategic deep dives for media companies

Your next step: modern data stack for your media company

Ready to transform your own infrastructure?

The MediaPrint infrastructure case study demonstrates that even complex media organizations with antitrust restrictions can be successfully modernized. The key is in Compliance-first architecture, use-case-driven approach and systematic transfer of knowledge.