Big Data refers to data sets that are too large, complex, and fast-changing to be managed by traditional data processing methods. These data are typically defined by three main characteristics:
Volume: Sources such as social media platforms, sensors, and business transactions generate billions of data points daily, highlighting the immense scale of modern data generation.
Velocity: Data is generated, collected, and processed at an incredible speed, often flowing continuously and requiring real-time analysis to keep up with rapid changes.
Variety: The data comes in different formats and from diverse sources. Structured data (e.g., table data in databases), semi-structured data (e.g., JSON files), and unstructured data (e.g., text or video data) contribute to the diversity of big data sets.
Big Data analytics is used to process these massive data piles and extract meaningful insights to improve decision-making processes. Technologies such as machine learning, artificial intelligence, data mining, and cloud computing play a critical role in analyzing big data.
