What are the big data technology platforms What are the big data basic platforms?

Index, National Bureau of Statistics, Business Information, Button Data, Promotion, 360 Big Data Platform, Yiche Index, AutoNavi Map, Mobile Observatory, iResearch.com.

Big data information is a large number of high-speed, and changeable with the help of big data tools and related technologies can be targeted marketing for users with different behavioral characteristics. At present, the top ten mainstream authoritative big data analysis platforms mainly include Alibaba, Tencent, AutoNavi Open Platform, Lubaozuo Big Data Research Institute, Umeng, Huawei Cloud Service, Inspur, Shenzhou Rong, and Hikvision.

1. Database & Data Platform, Transwarp. A big data platform company focusing on the Hadoop ecosystem. Hadoop is open source, Transwarp optimizes the unstable parts of Hadoop, refines the functions, and provides Hadoop big data engine and database tools for all enterprises.

2. Big data storage hardware, Inspur. Inspur is a very old IT company, which has been steadily researching and storing big data, and is leading in big data storage in China. 3. Cloud big data, Alibaba.

Not to mention this, the star product - Alibaba Cloud, competes with Amazon AWS and does public cloud, private cloud, and hybrid cloud.

4. In terms of data application, Finesoft and Haiyun data.

Domestic big data platforms include:

1. Transwarp. Transwarp is a large data platform company based on the Hadoop ecosystem, which has been named in the Gartner Magic Quadrant, and its potential cannot be ignored, with technical optimizations for the unstable parts of Hadoop, improved functionality, and an enterprise big data engine for Hadoop.

2. It belongs to an independent third-party brand. Its products and services cover a variety of highly targeted products and services such as mobile application data statistics, public data query, and comprehensive data management. It has a wide range of data service applications in the banking, Internet, and e-commerce industries.

3. Umeng+. Umeng+ is the first third-party global big data service provider, which can fully cover PCs, wireless routers and other devices. Provide enterprises with data application solutions for the whole business chain such as basic statistics, operation analysis, and data decision-making, and help enterprises carry out data operation and management.

4. NetEase Mammoth. NetEase Mammoth Big Data Platform provides a one-stop data management platform for massive application development, including big data development kits and Hadoop releases. The suite includes data development, task operations, self-service analytics, and multi-tenant management.

5. It is a data analysis product based on Internet user behavior, with non-buried data collection technology, which can conduct real-time analysis of user behavior data through behavioral data, such as browsing tracks, click records, mouse sliding tracks and other behavioral data of web pages or apps, so as to optimize product experience and achieve lean operation.

6. Sensors data. The principle of Sensors Data is also similar to that of GrowingIO. But it technically provides an open query API and a full SQL interface, while seamlessly integrating with compute engines such as MapReduce and Spark to access clean, regulated data in the most efficient way at any time.

1. Horizontal expansion

In recent years, with the increasing speed of data volume, traditional channel storage and computing can encounter bottlenecks, and big data channels are distributed architecture.

Theoretically, it can be expanded indefinitely, so it can better adapt to the development of the era.

2. Share resources

Through the use of a single cluster, enterprises can integrate all available server resources, and provide all talents to the outside world consistently, and can complete a fine-grained resource scheduling mechanism. In addition, only one cluster needs to be maintained, reducing O&M costs.

3. Data sharing

With a single storage architecture, all data within the enterprise can be gathered in a cluster, which is convenient for various transactional data.

so as to make full use of the advantages of full data analysis of big data skills.

4. Share the service

After the consistent service architecture, a set of consistent service design rules can be applied to all service completions, for example, a table data can be shared in the form of a file or an interface for sharing, and after we are consistent, each department can call and use it in the same way, avoiding the chimney architecture and directly reducing the cost of repeated development.

5. Safety assurance

Through a consistent security architecture, fine-grained resource blocking is completed on the basis of a single cluster architecture, and different levels of authorization are carried out for different personnel.

The big data service platform is a platform that integrates data access, data processing, data storage, query retrieval, analysis and mining, application interfaces, etc., and then provides data resources and data capabilities to drive business development services in a first-class way.

Computer, commonly known as computer, is an electronic computer used for high-speed calculation, which can perform numerical calculations, logical calculations, and also has the function of storage and memory. It can run according to the program and process massive amounts of data automatically and at high speed.

of modern smart electronic devices. A computer that consists of a hardware system and a software system without any software installed is called bare metal.

It can be divided into supercomputers.

Industrial control computers, network computers, personal computers.

There are five types of embedded computers, and the more advanced computers include biological computers, photonic computers, and quantum computers.

Neural network computers. Protein computers, etc.

1. Data-driven transactionsThrough data products and data mining models, the intelligence of enterprise products and operations is realized, and then the overall efficiency output of the enterprise is greatly improved. The most common application areas include precision marketing services based on personalized recommendation technology, advertising services, risk control and anti-fraud services based on model algorithms, credit services, etc.

2. External data monetizationAfter the data is carefully packaged, the data service is provided to the outside world, and then the cash income is obtained. It is common for big data companies to use their own big data to provide risk control inquiry, verification, anti-fraud services, customer guidance, diversion, precision marketing services, and data open channel services.

3. Data-assisted resolution planProvide basic data calculation report analysis services for enterprises. Analysts can easily obtain data output analysis reports to guide products and operations, product managers can improve product functions and improve user experience through computing data, operations personnel can find operational problems and determine the strategy and direction of operations through data, and management can grasp the company's business operations through data, and then make some strategic decisions and plans.