inspired by the rise of Small Data trends, this blog explores the evolving relationship and balance between Big Data and Small Data. Defining Small Data as human-comprehensible information providing context to Big Data, the article highlights the challenges of interpreting large datasets and biases in analysis. Ultimately, it advocates for a balanced approach, using both Big Data for trends and Small Data for context, facilitated by tools like FME, to achieve more meaningful insights in data analytics.