云计算与大数据相关技术(云计算与大数据应用与技术)

The key technologies of big data cover data storage, processing, application and other aspects. According to the processing process of big data, it can be divided into big data Collection, big data preprocessing, big data storage and management, big data processing, big data analysis and mining, big data display, etc.

1. Big data collection technology

Big data collection technology refers to obtaining various types of structured data through RFID data, sensor data, social network interaction data and mobile Internet data. , semi-structured and unstructured massive data.

Because data sources are diverse, the amount of data is large, and the speed of data generation is fast, big data collection technology also faces many technical challenges. It is necessary to ensure the reliability and efficiency of data collection, and to avoid duplication of data. .

2. Big data preprocessing technology

Big data preprocessing technology mainly refers to the completion of the analysis, extraction, cleaning, filling, smoothing, merging, normalization and processing of received data. Check consistency and other operations.

Because the acquired data may have multiple structures and types, the main purpose of data extraction is to transform these complex data into a single or easy-to-process structure in order to achieve rapid analysis and processing.

3. Big data storage and management technology

The main purpose of big data storage and management is to use memory to store the collected data, establish a corresponding database, and manage and manage it. transfer.

4. Big data processing

There are many types of big data applications, and the main processing modes can be divided into two types: stream processing mode and batch processing mode. Batch processing is stored first and then processed, while stream processing is processed directly.

Extended information:

Big data is everywhere and is used in various industries, including finance, automobiles, catering, telecommunications, energy, physical fitness and All walks of life, including entertainment, have been imprinted with big data.

1. Manufacturing industry, using industrial big data to improve the level of manufacturing industry, including product fault diagnosis and prediction, analysis of process flow, improvement of production process, optimization of production process energy consumption, industrial supply chain analysis and optimization, production Planning and Scheduling.

2. In the financial industry, big data plays a major role in the three major financial innovation fields of high-frequency trading, social sentiment analysis and credit risk analysis.

3. In the automotive industry, driverless cars using big data and Internet of Things technology will enter our daily lives in the near future.

4. In the Internet industry, with the help of big data technology, customer behavior can be analyzed, product recommendations and targeted advertising can be made.

5. In the telecommunications industry, big data technology is used to analyze customer off-grid, timely grasp the tendency of customers to leave the grid, and introduce customer retention measures.

Reference source: Baidu Encyclopedia - Big Data

Recently, a new term has become popular on the Internet, which is cloud computing, so many people have begun to wonder, what is cloud computing? What does it do? Huoying Computer Training will give you a detailed introduction below.

The virtual space of cloud computing is infinite. The large amount of data generated by the Internet of Things and the Internet needs to be stored and processed in a centralized place. Cloud for storage. For example, when we usually don’t have enough storage space on our mobile phones or computers, we will store some pictures and videos in cloud disks and clouds.

Cloud computing, simply put, is to put the hard disk and CPU in your own computer or on the company's server on the Internet, and call them uniformly and dynamically. The most famous cloud computing service provider now is Amazon's AWS. In the past, if you wanted to play the latest large-scale 3D game or make a large-scale 3D animation that needed to be rendered, the first thing you thought of was to buy a new computer with a higher configuration or change the graphics card;

With cloud computing, you only need a monitor and connect it to the cloud computing platform of the service provider. If you want to play new games for two days, you can separately purchase the high-end CPU and graphics card for these two days and only pay It costs two days, and when you get tired of playing, you can return to the normal configuration; if you want to do a lot of rendering tonight, buy the high configuration for a few hours tonight, and then you can restore the original configuration when you get the finished film the next morning. All these calculations and rendering work are completed uniformly in the data center of the cloud computing service provider. You only need to bill by the hour or even by the minute, and you no longer need to buy your own computers and servers. Cloud computing service providers will build their own data centers.

Big data, simply put, is to put all data together to analyze, find correlations, and achieve predictions. All the data here correspond to part of the data obtained from previous sampling surveys. For example, the traditional market research method is to go to the street or send out questionnaires online. It would be great to get hundreds or thousands of results, or invite a few typical users to a conference room for interviews; the approach of big data is to collect everyone’s information Analyze the data and analyze each person as an independent individual instead of looking for group characteristics. The result of big data is more accurate, more detailed and more personalized.

For another example, we often watch some modern spy movies. How does the reconnaissance department find criminals? It is to search for a person's face in massive data through the city's surveillance video. As long as the criminal appears in the surveillance, a piece of data and location will be retained, so as to better implement the next step and greatly improve the efficiency of solving crimes. This is why enterprises are strongly pursuing cloud computing big data technology. Another example is , Taobao, Toutiao, Sina, Baidu, NetEase and other shopping websites, which use this technology.

Big data and cloud computing are currently and in the future hot technology fields, with broad development prospects and job markets. This article will introduce methods and techniques for learning big data and cloud computing to help readers better master these technologies.
🔍Master core technologies and tools
In the fields of big data and cloud computing, it is very important to master some core technologies and tools, such as Hadoop, Spark, Kafka, Docker, Kubernetes, etc.
🎓Technical secondary school is a good starting point
If you have certain computer foundation and programming experience, it is not difficult to learn big data and cloud computing. Technical secondary school is a good starting point. You can choose to learn relevant basic courses and programming languages, such as Java, Python, etc. during technical secondary school.
📚Self-study of commonly used tools and frameworks
Then you can self-study some commonly used big data and cloud computing tools and frameworks, and understand their principles and usage.
💻Online Learning Platform
In addition, you can also learn related courses through some online learning platforms, such as Coursera, Udemy, edX, etc. These platforms provide a wealth of courses and practical projects, which can Help you learn and master relevant knowledge and skills more deeply.
👍Continuous learning and practice
In short, learning big data and cloud computing requires a certain amount of patience and perseverance, but through continuous learning and practice, you can gradually master these technologies and prepare for your career development Lay a good foundation.