What are the four basic characteristics of big data
The four basic characteristics of big data are: 1. Large amount of data; 2. Rapid response required; 3. Data diversity; 4. Low value density. Big data refers to a collection of data that cannot be captured, managed, and processed within a certain time frame using conventional software tools.
Introduction to the four basic characteristics of big data:
1. Large data volume
TB, PB, or even EB Data of equal volume requires data analysis and processing.
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2. Require quick response
The market changes quickly and requires timely and rapid response to changes. Data analysis must also be fast and have higher performance. requirements, so the amount of data seems to be a bit "large" in terms of speed requirements.
3. Data diversity
There are more and more unstructured data from different data sources, which need to be cleaned, organized, filtered and other operations to turn into structured data.
4. Low value density
Due to untimely data collection, incomplete data samples, incomplete data, etc., the data may be distorted, but when the amount of data reaches a certain scale, it can Achieve more realistic and comprehensive feedback through more data.
Big data (big data), an IT industry term, refers to a collection of data that cannot be captured, managed, and processed with conventional software tools within a certain time range. It requires new processing models to make stronger decisions. Massive, high-growth and diversified information assets with powerful capabilities, insights and process optimization capabilities.
In the "Big Data Era" written by Victor Meyer-Schonberg and Kenneth Cukier, big data refers to the use of all data instead of shortcuts such as random analysis (sampling survey). Analysis and processing. The 5V characteristics of big data (proposed by IBM): Volume, Velocity, Variety, Value, and Veracity.
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