What is the use of a big data collection system?

First, the processing and analysis of big data is becoming a new generation of information technology.

Converge the nodes of the application. Mobile Internet.

Internet of Things, social networks.

Digital home, e-commerce, etc. are the application forms of a new generation of information technology, and these applications continue to generate big data. Cloud computing provides a storage and computing platform for these massive and diverse big data. Through the management, processing, analysis and optimization of different data, the results will be fed back into the above applications, which will create great economic and social value.

Second, big data is an information industry.

A new engine for sustained and high-speed growth. New technologies, new products, new services, and new business formats for the big data market will continue to emerge. In the field of hardware and integrated equipment, big data will have an important impact on the chip and storage industries, and will also give rise to integrated data storage and processing servers, memory computing and other markets.

In the field of software and services, big data will lead to the development of rapid data processing and analysis, data mining technology and software products.

Third, the use of big data will become a key factor in improving core competitiveness. Decision-making across industries is shifting from "business-driven" to "data-driven."

1. Big data is a large amount of high-speed, changeable information, which requires new processing methods to promote stronger decision-making ability, insight and optimal processing. Big data provides unprecedented space and potential for enterprises to gain deeper and more comprehensive insights.

2. With the help of big data and related technologies, we can carry out targeted marketing for customers with different behavioral characteristics, and even from "recommending a product to some suitable customers" to "recommending some suitable products to a customer", so as to focus more on customers and carry out personalized precision marketing.

3. The era of big data.

Precision marketing refers to obtaining the preferences and behavioral preferences of objects through big data, and conducting different marketing for different objects. The core of big data precision marketing can be summarized into several key words: user, demand, identification, and experience.

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As follows:

2. The principle of integrity: information collection must be in accordance with certain standard requirements, collect information that reflects the whole picture of things, and the principle of integrity is the basis of information utilization.

3. Real-time principle: the time interval from the occurrence of information to the collection, the shorter the interval, the more timely it is, and the fastest is the synchronization of information collection and information.

4. The principle of accuracy: the expression of the collected information is correct, belongs to the scope of the purpose of collection, and is applicable and valuable relative to the enterprise or organization itself.

6. The principle of foresight: information collectors should grasp the development trends of society, economy and science and technology, keep abreast of the future, and collect information that has a guiding role in future development.

Channels for information collection:

1. Traditional information system. The information collected by traditional information systems often has high value, on the one hand, because traditional information systems often collect structured data, which is easy to count and analyze, and on the other hand, because the data collected by traditional information systems are often more important data.

2. Web platform. With the popularization of web applications, especially after the popularization of applications, the entire web system has generated a large amount of data, which is also one of the important data of the big data system.

3. Internet of Things system. The Internet of Things is very closely related to big data, and unlike traditional information systems and web systems, most of the data of the Internet of Things is unstructured data and semi-structured data, and specific processing methods are required to analyze it, including batch processing and stream processing.

With the continuous development of the Internet, the use of big data has become more and more common, and has become the hottest application in the IT industry. What is big data? Big data refers to a collection of data that is acquired, managed, and processed by conventional software tools over a period of time.

These include massively parallel processing (MPP) databases, data mining grids, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems. So what is big data used for? The following computer training is for you to introduce in detail.

1. Big data processing and analysis has become the node of the integration and application of a new generation of information technology. At present, mobile Internet, Internet of Things, social networks, digital homes, e-commerce, etc. are the application forms of a new generation of information technology, which can continuously generate a large amount of data.

2. The big data information industry is a new engine for sustained and rapid development. New technologies, new products, new services, and new forms of business are emerging one after another. In the field of hardware and integrated devices, it has an important impact on the chip and storage industries, and IT training has found that integrated data is stored in the market such as processing servers and memory computing.

3. The use of big data resources will be a key factor in improving core competitiveness. Decisions across industries are shifting from "business-driven" to "data-driven". Beida Jade Bird believes that by analyzing a large amount of data, retailers can grasp market trends in real time and respond quickly.

Businesses can provide decision-making support to develop more accurate and effective marketing strategies.

4. In the era of big data, the methods of scientific research have undergone significant changes. In the era of big data, through real-time monitoring, tracking a large number of behavioral data of research subjects on the Internet, mining and analysis, Kunming Beida Jade Bird found that there are regular data, and research conclusions and countermeasures can be proposed.

Data collection technology refers to the completion of data acquisition from the source and transmission to the big data platform for data governance and data service use. Data refers to various types of structured, semi-structured (or weakly structured) and unstructured massive data obtained through RFID radio frequency data, sensor data, social network interaction data and mobile Internet data, which is the foundation of the big data knowledge service model. It is important to break through big data collection technologies such as distributed, high-speed, high-reliability data crawling or collection, and high-speed data full image; Breakthrough in high-speed data analysis, conversion and loading and other big data integration technologies; Design quality assessment models and develop data quality techniques.

Oceanmind data collection includes public data collection and collection aggregation tools.

Public data collection is mainly biased towards the collection and aggregation of Internet open data, and public data collection is a flexible, convenient, efficient and scalable Internet data crawler system. Templates can be used to crawl data from designated public web pages and provide them for subsequent data processing.

The collection and aggregation tool is biased towards the collection and aggregation of holding-type data, and the aggregation tool is a visual data collection software, in which the external data is converted into a file of the database or file type (CSV, Parquet) and stored in the specified FTP path through the collection tool, and then the FTP silly girl's files are aggregated to the big data platform through the aggregation tool.

Data acquisition technology is widely used in various fields. For example, cameras and microphones are all data collection tools.

Generally speaking, data collection should collect as much data as possible from data sources such as target objects, devices, and services, and transmit and summarize the obtained data to the designated area for storage in the form required, so as to lay the foundation for future data mining and analysis.

1.Data quality controlWhenever a variety of data sources are used, data quality is a challenge. This means that the job of the organization must be to ensure that the data formats are accurately matched and that there is no duplicate data or lack of data that leads to unreliable analysis.

Businesses must analyze and prepare data in advance before they can analyze it alongside other data.

2.ExpandThe use value of big data depends on its quantity. However, this will also become a key problem.

If you don't design an architecture to start scaling, you're going to quickly face a series of problems. First, if enterprises do not prepare for infrastructure construction, then the cost of infrastructure construction will increase. This will put pressure on the company's expense budget.

Second, if the company is not ready to expand, then its characteristics will be significantly reduced. Both of these challenges should be addressed in the overall planning of building a big data architecture.

3. Safety factorWhile big data can provide organizations with deeper insights into their data, protecting it can be challenging. Fraudsters and cyber hackers will be so interested in a company's data that they will try to add their own fake data or access the company's data to obtain sensitive information.

1. Offline collection: Tool: ETL; In the context of data warehousing, ETL is basically a representation of data collection, including extracting, transforming, and loading data.

In the process of transformation, it is necessary to govern data for specific business scenarios, such as illegal data monitoring and filtering, format conversion and data standardization, data replacement, and data integrity. 2. Real-time collection: tools:

flume/kafka；Real-time collection is mainly used in business scenarios considering stream processing, for example, to record various operational activities performed by data sources, such as traffic management for network monitoring, accounting for financial applications, and user access behaviors recorded by web servers. In the stream processing scenario, data collection becomes a consumer of Kafka, which acts like a dam to intercept the data of the upstream car, and then perform corresponding processing (such as deduplication, denoising, and intermediate computing) according to the business scenario, and then write it to the corresponding data store. This process is similar to the traditional ETL, but it is a streaming processing method, rather than a scheduled batch job, and these tools use a distributed architecture to meet the requirements of hundreds of MB per second log data collection and transmission

Tools: crawler, dpi, etc.; SCRIBE is a data (log) collection system developed by Facebook. Also known as web spider, web robot, is a program or script that automatically scrapes information from the World Wide Web according to certain rules, and it supports the collection of files or attachments such as **, audio, **.

Big data collection can be achieved by using an octopus collector. Octopus Collector is a comprehensive, simple and widely applicable Internet data collector. It can help users quickly scrape all kinds of data on the Internet, including text, **, ** and other formats.

Octopus Collector is simple to use and fully visualized, no need to write**, built-in massive templates, and supports arbitrary network data scraping. If you need to collect big data, Octopus Collector can provide you with intelligent identification and flexible custom collection rule settings to help you quickly obtain the required data. To learn more about the functions of the octopus collector and the cooperation of the god banquet case, please go to the official website for more details of Tongdu.