What are the characteristics of big data?

Characteristics of big data: 1. Capacity; the size of the data determines the value and potential information of the data considered. 2. Type; diversity of data types. 3. Speed; the speed of obtaining data. 4. Variability; hinders the process of processing and effectively managing data. 5. Authenticity; quality of data. 6. Complexity; huge amount of data from multiple sources. 7. Value: Rational use of big data to create high value at low cost.

The operating environment of this tutorial: Windows 7 system, Dell G3 computer.

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 Meier-Schoenberg 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 (capacity), Velocity (high speed), Variety (diversity), Value (low value density), and Veracity (authenticity).

Characteristics of big data

• Capacity (Volume): The size of the data determines the data considered The value and potential information;

• Variety: the diversity of data types;

• Velocity: refers to obtaining data Speed;

• Variability (Variability): hinders the process of processing and effectively managing data.

• Veracity: The quality of data.

• Complexity: The amount of data is huge and comes from multiple channels.

• Value (value): Rational use of big data to create high value at low cost.

The value of big data is reflected in the following aspects:

(1) For large-scale consumption Enterprises that provide products or services can use big data for precision marketing;

(2) Small, medium and micro enterprises with a small but beautiful model can use big data for service transformation;

(3) Traditional enterprises that must transform under the pressure of the Internet need to keep pace with the times and make full use of the value of big data.

However, the great significance of "big data" in economic development does not mean that it can replace all rational thinking on social issues. The logic of scientific development cannot be lost in massive data. The famous economist Ludwig von Mises once reminded: "Today, many people are busy with the useless accumulation of data, so that they have lost their understanding of the special economic significance in explaining and solving problems. .” This is indeed something we need to be vigilant about.

In this rapidly developing era of smart hardware, an important issue plaguing application developers is how to find the delicate balance between power, coverage, transmission rate and cost. Business organizations leverage relevant data and analytics to help them reduce costs, increase efficiency, develop new products, make smarter business decisions, and more. For example, by combining big data and high-performance analysis, the following situations that are beneficial to the enterprise may occur:

(1) Timely analysis of the root causes of faults, problems and defects may save the enterprise tens of thousands of dollars every year One hundred million U.S. dollars.

(2) Plan real-time traffic routes for thousands of express vehicles to avoid congestion.

(3) Analyze all SKUs, price and clear inventory with the goal of maximizing profits.

(4) Based on the customer’s purchasing habits, push preferential information that he may be interested in.

(5) Quickly identify gold medal customers from a large number of customers.

(6) Use click stream analysis and data mining to avoid fraud.

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