What is big data and how do you get started?

Big data is divided into four characteristics as a whole, first, a large number of them.

The unit of measurement is petabyte level, and there are many storage contents.

Second, high speed.

Third, diversity.

Fourth, value.

Big data not only has its own information value, but also has business value. Big data is also structurally divided into: structured, semi-structured, and unstructured.

Structured is simply a database, which is data that is logically expressed and implemented by two-dimensional tables. Unstructured means that the data structure is irregular or incomplete, and there is no predefined data model. Much of the data generated by humans is unstructured.

Definition of big data: Big data, also known as big data, refers to the amount of data involved that is so large that it cannot be captured, managed, processed, and sorted into information that can be captured, managed, processed, and sorted into a more positive purpose for business decision-making through the human brain or even mainstream software tools within a reasonable time. Netboat Technology is based on mobile Internet data collection, analysis of user behavior, through data mining means, to achieve the whole process of data analysis solutions.

The analysis tool used is currently the most advanced in the industry, Adobe Insight.

The characteristics of big data: large amount of data, many types of data, strong real-time requirements, and large value of data. Big data exists in all walks of life, but a lot of information and consultation are complex, and we need to search, process, analyze, summarize, and summarize its deep-seated rules.

Big data collection: The development of science and technology and the Internet has promoted the advent of the era of big data, and all walks of life are generating a huge number of data fragments every day, and the data measurement unit has developed from bytes, kb, mb, gb, and TB to PB, EB, ZB, YB, and even bb, nb, and db. In the era of big data, the collection of data is no longer a technical problem, but in the face of so much data, how can we find its internal laws.

Mining and processing of big data: Big data must not be calculated and estimated by the human brain, or processed by a single computer, and must adopt a distributed computing architecture, relying on the distributed processing, distributed database, cloud storage and virtualization technology of cloud computing, therefore, the mining and processing of big data must use cloud technology.

1. Ensuring network security. Establish a starting point with terminal security management as the core, and build a complete terminal protection system from data protection, terminal control, security management, desktop management, etc.

2. Maintain information operation. The ultimate goal of big data is to be able to apply the acquired data to provide services and generate value.

Big data helps to maintain the information operation of enterprises and assist enterprises in their application.

Big data refers to a general term under the large amount of information under today's developed network!

Presumably, many people have heard of big data now, so what is big data? What can big data do? Let me explain to you what big data is.

01 Big data, as the name suggests, refers to a large collection of data, specifically the collection of data that cannot be captured, managed, and processed by conventional software tools in an affordable time frame.

02 Of course, big data requires a new processing model to have stronger decision-making, insight and process optimization capabilities to adapt to massive, high-growth and diversified information assets.

03 Big data has many applications, such as data collection and storage, and then analysis and application.

04 In addition, on the basis of the analysis of data, our products and services are formed, and the products and services will also generate new data, and these new data will be recycled into our processes.

At present, big data has been widely used in marketing, finance, industry, medical care, education, transportation, insurance, law enforcement, sports, tourism, logistics and other fields.

In a word, big data is all about managing and leveraging large amounts of data.

Separately, it is how to generate data, how to transport data, how to store data, how to effectively organize data for easy use, how to process data and improve value, how to use data, and manage the entire life cycle.

Data generation: is the source of data, how do we produce data. There are business data, such as user tables in MySQL, front-end buried points (monitoring every operation of users), log data output by programs, and data crawled by crawlers.

With so much data at its source, we need a data source of how to generate data.

Data access: How to move data from so many sources to the data center for unified processing. How to use to carry it, build a pipe to let it come in all the time, or carry it every once in a while, this is all to consider.

Data storage: how to store a large amount of data so that it will not be lost and read quickly.

Data warehouse: How to effectively manage data is something that should be considered by data warehouse.

Data calculation: A large amount of data needs to be processed in order to generate value, so the efficiency of the processing tool affects your efficiency.

Data Applications: What data can be used for.