Unstructured data, or approximately 90% of new corporate data, is growing 300% faster than structured data, posing significant challenges in terms of storage and analysis. This growth is crucial for analyzing and predicting social policies with personal data, including emails, GPS locations, and smart objects, forming the Internet of Everything (IoE). The rapid accumulation of Big Data has transformed data handling methods, highlighting unstructured data’s potential, aligning with Simondon’s concepts of preindividuality and metastability. Simondon’s interdisciplinary approach views information as dynamic, with technical ensembles (e.g., cloud computing) promoting the individuation and evolution of data systems. These systems resemble living organisms, where technical evolution leads to greater integration and functional convergence. This progression emphasizes the need to adapt data handling methods beyond traditional structured paradigms to fully leverage the value of extensive unstructured data sets.