Big data 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 have stronger decision-making power, insight discovery and process optimization capabilities. of massive, high-growth and diversified information assets. Features: Large volume, high speed, variety, low value density, authenticity.
Big data (big data), an IT industry term, refers to a collection of data that cannot be captured, managed and processed within a certain time range using conventional software tools. , are massive, high-growth and diversified information assets that require new processing models to have stronger decision-making power, insight discovery 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 (large amount): Huge amount of data
Centralized storage/centralized computing can no longer handle the huge amount of data.
The amount of data is growing exponentially: sensors in earthquakes, well logging, and oil rigs generate more data in one month than all the movies in the world combined.
Sina Weibo has 250 million users, with a peak of several hundred million messages per day.
Variety: Unstructured data diversity
Text/picture/video/document, etc., such as micro-seismic, electromagnetic and optical fiber distributed temperature monitoring (DTS).
Velocity (high speed): fast data growth
Huge user base/large number of devices/massive real-time/exponential growth of data.
Value (low value density): The value of the data
Each drilling rig has 40,000 sensors, but typically only 10% of the data is used.
The investment in each deepwater drilling platform can reach $150M. It is critical to effectively utilize all data, which is related to safety and optimized operations.
Vercity (authenticity): the authenticity of the data
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