Content, Data, and Process Models for Performing Data Analyses

This paper presents a methodology for the standardized execution of data analyses, enabling organizations to perform more reliable, transparent, and efficient analytical work. The approach is based on a unified content framework, a data model, and a clearly structured process that ensures consistency and traceability for analysts while improving end users’ understanding of the results. By defining key data elements and their relationships, the data model ensures that analyses are built on verified, comparable, and properly documented information. Special emphasis is placed on data quality, which critically shapes the reliability of analytical conclusions and the decisions derived from them. The methodology covers the entire data analysis lifecycle—from request formulation and selection of data sources to data quality verification, algorithm preparation, result validation, and final presentation of findings. Such an approach provides organizations with a robust analytical framework that supports the development of advanced data solutions and enhances both strategic and operational decision-making.