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Data is a critical aspect of the world we live in. With systems producing andconsuming vast amounts of data, it is essential for businesses to digitallytransform and be equipped to derive the most value out of data. Data analyticstechniques can be used to augment strategic decision-making. While this overallobjective of data analytics remains fairly constant, the data itself can beavailable in numerous forms and can be categorized under various contexts. Inthis paper, we aim to research terms such as 'small' and 'big' data, understandtheir attributes, and look at ways in which they can add value. Specifically,the paper probes into the question "If we didn't solve small data in the past,how can we solve Big Data today?". Based on the research, it can be inferredthat, regardless of how small data might have been used, organizations canstill leverage big data with the right technology and business vision.

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