Jesse Anderson highlights the common misconception that having a large quantity of data, such as 3 billion rows or 100 GB, automatically necessitates the use of Big Data technologies, emphasizing that this is not always the case and that small data technologies might be more suitable in such scenarios. He argues that small data solutions, like cloud data warehouses, often offer advantages such as less complexity, lower costs, and faster query speeds, making them a better fit for many use cases that do not truly require Big Data capabilities. Anderson also identifies scenarios where Big Data is genuinely needed, such as dealing with hundreds of billions of rows or petabytes of data, and stresses the importance of having a well-trained team and realistic project expectations. He warns against the tendency to overestimate Big Data as a cure-all solution, noting that companies should tailor their approach based on specific use cases rather than applying a one-size-fits-all methodology.