"If we didn't solve small data in the past, how can we solve Big Data\n today?"

Data is a critical aspect of the world we live in. With systems producing and\nconsuming vast amounts of data, it is essential for businesses to digitally\ntransform and be equipped to derive the most value out of data. Data analytics\ntechniques can be used to augment strategic decision-making. While this overall\nobjective of data analytics remains fairly constant, the data itself can be\navailable in numerous forms and can be categorized under various contexts. In\nthis paper, we aim to research terms such as 'small' and 'big' data, understand\ntheir attributes, and look at ways in which they can add value. Specifically,\nthe paper probes into the question "If we didn't solve small data in the past,\nhow can we solve Big Data today?". Based on the research, it can be inferred\nthat, regardless of how small data might have been used, organizations can\nstill leverage big data with the right technology and business vision.\n