Definition: Data is defined as the quantities, characters, or symbols on which operations are performed by a computer. It can be stored and transmitted and recorded on various media.
Examples: Text, numbers, images, audios, and videos stored digitally as zeros and ones.
Terminology: 'Data' is plural; the singular is 'datum'.
What is Big Data?
Definition: Big Data refers to extremely large data sets that cannot be processed or analyzed using traditional tools.
Characteristics: The data volume increases exponentially, e.g., more than 500 terabytes are uploaded to Facebook daily.
Importance of Big Data
Benefits:
Netflix Example: Uses Big Data to analyze user behavior, recommend shows, and improve customer retention.
Credit Card Companies: Use real-time data to detect fraud by analyzing geographical usage patterns.
Applications: Big Data is utilized in various fields like banking, communication, healthcare, media, manufacturing, transportation, and retail.
Classification of Big Data
Big Data is classified into three main types:
1. Structured Data
Definition: Ordered data stored in databases, accounting for about 20% of all data.
Sources:
Machine-Generated: Includes data from sensors, weblogs, GPS, medical devices, and trading platforms.
Human-Generated: Data input by humans like personal details and online interactions.
2. Unstructured Data
Definition: Data without a clear format, making up about 80% of all data.
Sources:
Machine-Generated: Satellite images, scientific and radar data.
Human-Generated: Social media data, mobile data, website content.
3. Semi-Structured Data
Definition: Appears unstructured but contains organizational properties for easier processing.
Example: NoSQL documents with keywords for processing.
Conclusion
Business Value: Analyzing Big Data can lead to cost reductions and growth for businesses.
Call to Action: Businesses should exploit Big Data opportunities promptly.
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