Adrian Large reports that ‘Big Data’ is a nebulous term. It refers to data so voluminous and complex that traditional data processes are inadequate to deal with it. It is also not necessarily always just about data size, but the speed at which data is processed, and the type of information. So Big Data is not a one size fits all term. It is vague jargon which means different things to different organisations. A seemingly nefarious concept by nature, Big Data is an integral fragment of understanding the digital age in mining by providing insight from information sources that are diverse, complex, and of immense scale.
Big Data enables timely decisions that are customarily difficult to execute without intensive workloads. It also amplifies organisational value, which among other things includes saving lives, determining patterns in abstract data (such as imagery), and exploring complex relationships between unrelated data sets that would not otherwise be detected. In other words, Big Data has the capacity to offer substantial benefits we cannot normally see.
Big Data consists of 3 different types of data structures. 1) Structured data: any data stored in a specific data scheme and typically recognized as tabulated such as SQL, Oracle, Excel, and Access. 2) Semi-structured Data: which does not conform to a regular data model, but through text based tags and markers enforces hierarchies of records and fields within the data. 3) Unstructured Data: data without a pre-defined data model such as reports, word documents, images, and video. These classifications are fundamental in understanding Big Data.
Big Data is relevant across the mining value chain. From exploration prospectivity mapping to managing autonomous machinery and safety. It offers the capacity to harness previously superfluous data, and make decisions that will improve safety, costs, and productivity over time.
The term Big Data will not be disappearing any time soon. By its very nature, Big Data infers massive volumes of data processed and analysed at speed beyond the realm of traditional data practices. Big Data platforms will always be searching for new technologies and innovations that are continuously improving.
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