What is an example of data that is not classified as big data?

What is an example of data that is not classified as big data?

• A. Data generated by social media platforms
• B. Data stored in a small relational database
• C. Data collected from sensors in IoT devices
• D. Data generated from online transactions

Answer: (B)

Data stored in a small relational database is not classified as big data primarily due to its volume, velocity, and variety. Big data typically refers to datasets that are exceptionally large in size or that exhibit high complexity and rapid generation rates, often requiring specialized tools and techniques for processing and analysis. In contrast, a small relational database, which might contain structured data with a limited scope and manageable size, does not meet these criteria. Such databases can generally be handled with traditional data processing methods and do not necessitate the advanced approaches used for big data analytics. Other examples, such as data generated by social media platforms, data collected from IoT devices, and data generated from online transactions, commonly involve vast amounts of information generated at high speed, thus fitting the profile of big data. These types of data are characterized by their large volume and the complexity of insights that can be derived from them, making them require more sophisticated analytics strategies.

Data stored in a small relational database is not classified as big data primarily due to its volume, velocity, and variety. Big data typically refers to datasets that are exceptionally large in size or that exhibit high complexity and rapid generation rates, often requiring specialized tools and techniques for processing and analysis.

In contrast, a small relational database, which might contain structured data with a limited scope and manageable size, does not meet these criteria. Such databases can generally be handled with traditional data processing methods and do not necessitate the advanced approaches used for big data analytics.

Other examples, such as data generated by social media platforms, data collected from IoT devices, and data generated from online transactions, commonly involve vast amounts of information generated at high speed, thus fitting the profile of big data. These types of data are characterized by their large volume and the complexity of insights that can be derived from them, making them require more sophisticated analytics strategies.