TIDK was established to spread the idea of a data-driven organization. We use the latest knowledge in technology, artificial intelligence, data, statistics, and mathematics, and we tailor our approach to the organization's needs and analytical development stage.

1. DATA-DRIVEN STRATEGY – Analysis, audits, concepts, and recommendations of the plan to implement the assumptions of the data monetization strategy within the organization. C-level workshops for a roadmap of analytical transformation, cloud adoption, and usability of AI.
2. DATA GOVERNANCE – Building concepts and standards for working with data in the organization, support in identifying processes and data, defining roles and responsibilities, defining the scope of data sources, indicators, and measures to be cataloged (metadata), establishing data quality rules.
3. KNOWLEDGE TRANSFER – Implementation according to up-to-date standards. Transparent work progress and risk reporting. Practical mentoring and support of the client's team through knowledge transfer and evangelization of good practices.
4. PARTNERSHIP AND SUPPORT – Frequent exchange of knowledge with mentors and flexibility in the approach to the implementation of dynamic business assumptions. Support in ongoing projects and redesign of existing solutions.

Since 2009, TIDK has been providing, designing, and implementing data-oriented solutions for European companies. The portfolio of offered solutions starts with data warehouses, integrations of data from various systems, reporting, monitoring, and data visualization systems. TIDK has experience in building and implementing proprietary models based on expert knowledge, classical machine learning methods, and deep learning. The company is also a leader in Data Science and Artificial Intelligence in Poland.

1. MODERN DATA PLATFORM – Concepts and projects of modern analytical solutions in Lakehouse and data mesh architectures, integration of data sources, business intelligence (models, visualizations, reports), real-time analytics, Big Data, and IoT.
2. DATA SCIENCE – Exploration and study of dependencies in data, process optimization, task scheduling, multi-criteria optimization, simulation models.
3. ARTIFICIAL INTELLIGENCE – Concept development, research, and implementation of dedicated algorithms (machine learning, deep learning), implementation of solutions in forecasting, anomaly detection, and recommendation systems.