Big data harmonisation for enhanced efficiency in real-world applications

Over four hundred million terabytes of data are generated daily. In the modern era, managing information from various sources poses a challenge because of its scale and speed (Marr, 2016; IDC, 2021; Muhammad, 2025). In 2024, for instance, there were roughly 5.9 million Google searches, 16,000 TikTok videos uploaded, and over 3.4 million YouTube views per minute, according to Eaves (2025). This sets new boundaries for businesses given the amount of semi-structured, unstructured, or structured data gathered from social platforms, machines, or transaction-based systems using traditional tools. Paying via apps, airline check-ins, and even medical record-keeping enables Internet of Things (IoT) devices, such as smartwatches, to gather valuable stream data online. The biggest blocker in such cases is the heterogeneity that big data presents because it includes numerous frameworks where standards, along with their accompanying qualities, are disparate. When experts are provided with vast amounts of fragmented information due to gaps created by silos or incompatible formats within data separated into chunks without any relation to each other’s reference system, they become “blind and deaf”.