Big Data:
Big data refers to a collection of data that cannot be captured, managed and processed by conventional software tools within a certain time frame. , high growth rate and diversified information assets. In "The Age of Big Data" written by Victor Mayer-Schönberger and Kenneth Cookyer, big data refers to the use of all data for analysis and processing without the shortcut of random analysis (sampling survey). The 5V characteristics of big data (proposed by IBM): Volume (large amount), Velocity (high speed), Variety (variety), Value (low value density), Veracity (authenticity).
For "big data" (Big data) research organization Gartner gave such a definition. "Big data" requires new processing modes to have stronger decision-making power, insight discovery power and process optimization ability to adapt to massive, high growth rate and diversified information assets.
The definition given by the McKinsey Global Institute is: a large-scale data collection that greatly exceeds the capabilities of traditional database software tools in terms of acquisition, storage, management, and analysis. Data type and low value density are four characteristics.
The strategic significance of big data technology is not to master huge data information, but to professionally process these meaningful data. In other words, if big data is compared to an industry, the key to making this industry profitable is to improve the "processing ability" of data, and to realize the "value-added" of data through "processing".
From a technical point of view, the relationship between big data and cloud computing is as inseparable as the two sides of a coin. Big data cannot be processed by a single computer, and a distributed architecture must be adopted. Its characteristic lies in the distributed data mining of massive data. But it must rely on the distributed processing, distributed database and cloud storage, and virtualization technology of cloud computing.
With the advent of the cloud era, big data has also attracted more and more attention. According to the analyst team, Big Data is often used to describe the large amount of unstructured and semi-structured data created by a company that would take too much time and money to download to a relational database for analysis. Big data analysis is often associated with cloud computing because real-time analysis of large data sets requires a MapReduce-like framework to distribute work to dozens, hundreds, or even thousands of computers.
Big data requires special techniques to efficiently process large volumes of data that tolerate elapsed time. Technologies applicable to big data, including massively parallel processing (MPP) databases, data mining, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems.
Alibaba Cloud University Internet College: Homepage of Big Data Development
Master the core technology of big data development and become a sought-after talent in the workplace ;
Combining theory with actual combat, playing with big data framework and storage computing, actual combat enterprise big data system development, starting from 0, growing into an excellent big data development engineer.
For people
Big data development enthusiasts and developers
Those who are ready to engage in big data development, other Internet practitioners or big data enthusiasts
study time
5 months
3 hours a week, master the core technology of big data development
prior knowledge
Development language basics
Basic knowledge of Java and SQL
Actual project
16 Scenario Projects
Famous teachers teach, master the latest skills of big data development practical projects
More details:
Homepage of the Internet College of Alibaba Cloud University (professional system class-based teaching, after graduation, you can get a certificate and find your ideal job)