
Data & AI Management
Data-driven decision-making and artificial intelligence projects cannot create long-term value without proper data management. Through our data governance and data engineering services, we make the company's data assets accessible and reliable.
We have already assisted them with our services:






01
What does Data and AI Management entail?
„Garbage in, Garbage out”
We can only create real value from corporate data assets if we make them accessible and reliable in the proper manner. Simultaneously, we must treat our data and the information derived from it as corporate assets.
Through our Data Engineering services, we support our clients in collecting, organizing, and making available the data assets within the company for the purpose of value creation.
In our Data Governance services, our primary focus is on a practical, realistic, and results-oriented approach. Instead of multi-year gigantic projects, we believe in a series of projects that are most aligned with the maturity level and business expectations, which, based on our experience, helps in gaining acceptance from Data Governance management.
Our DataOps approach is a practical complement to Data Governance programs, but based on our experience, it also provides significant added value independently in reducing business risks.
AI Act readiness / Artificial Intelligence model management: Responsible AI development and application is no longer just a "nice" principle but an approach expected by the EU as well. We support our clients in establishing AI management compliant with the AI Act, cataloging models, risk-based evaluations, developing review plans, and testing/validation of models.
02
For those it's useful for:
Data Science, AI, and ML fields
Business area leaders
Leaders in the Data Engineering field
Risk Management leaders
IT Governance leaders
03
In what cases does Data and AI Management provide solutions?
- Lack of, or inadequate quality of available data
- Elimination of data silos
- Creation of a 360-degree customer view
- Addressing data quality issues
- Preparation for AI Act compliance
- Validation of Artificial Intelligence models

Testing and Automating a Mobile App in the Global Online Gaming Industry
Manual testing, Automated testing, Test management
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