The correct answer is D. All of the mentioned.
Big data is a term that describes the large volume of data â both structured and unstructured â that inundates a business on a day-to-day basis. But itâs not the amount of data thatâs important. Itâs what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
The data growth and social media explosion have changed how we look at the data. We now have access to more data than ever before, and it is coming from a variety of sources, including social media, sensors, and mobile devices. This data can be used to track customer behavior, identify trends, and make better decisions.
However, big data is not just about lots of data. It is also about the ability to store, process, and analyze large amounts of data quickly and efficiently. This requires new technologies and techniques, such as Hadoop and Spark.
Big data is a powerful tool that can be used to improve business performance. However, it is important to remember that big data is not a silver bullet. It is only as good as the insights that are extracted from it.
Here is a brief explanation of each option:
- Option A: The big volume indeed represents Big Data. This is true. Big data is characterized by its large volume. The amount of data that is being generated every day is staggering. In 2020, it was estimated that 2.5 quintillion bytes of data were created every day. This number is expected to grow to 463 exabytes by 2025.
- Option B: The data growth and social media explosion have changed how we look at the data. This is also true. The data growth and social media explosion have made it possible to collect and store more data than ever before. This data can be used to track customer behavior, identify trends, and make better decisions.
- Option C: Big Data is just about lots of data. This is not true. Big data is not just about lots of data. It is also about the ability to store, process, and analyze large amounts of data quickly and efficiently. This requires new technologies and techniques, such as Hadoop and Spark.
Therefore, the correct answer is D. All of the mentioned.