What does big data mean It s a little easier to understand

It refers to the collection of data that can no longer be captured, managed and processed by conventional software tools within a certain time frame, and it is necessary for new processing models to have stronger decision-making power, insight discovery and process optimization capabilities to adapt to massive, high-growth rate and diversified information assets——— Lemon Academy Big Data Training for NIN Solution.

Does Big Data Spend in Online Lending Affect Loans?

What is Big Data? In the eyes of many people, big data may be a very vague concept, but in daily life, big data is very close to us, and we no longer enjoy the convenience, personalization and humanization brought to us by big data all the time.

To understand big data comprehensively, we should have a brief understanding of four aspects.

Definition, structural characteristics, what big data is around us, and what big data brings, these four aspects are understood.

So what exactly is "big data"?

According to the definition given by the McKinsey Global Institute, big data is a collection of data that is so large that it is far beyond the capabilities of traditional database software tools in terms of acquisition, storage, management, and analysis. To put it simply, big data is a lot of data.

The unit of big data is generally measured in petabytes. So how big is PB? 1GB = 1024MB, 1PB = 1024GB is enough to be called big data.

Secondly, what are the characteristics and structure of big data?

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.

Second, diversity.

Third, 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.

So what are the things around us that are big data?

Summary. Big data refers to the collection of data that cannot be captured, managed, and processed by conventional software tools within a certain time frame, and is a massive, high-growth and diversified information asset that requires new processing modes to have stronger decision-making, insight and process optimization capabilities.

Hello dear, glad to answer for you. Big data (big data), or big data, refers to the amount of data involved that is so large that it is impossible to capture, manage, process, and organize information that can be used to help enterprises make business decisions more balanced in a reasonable period of time.

Big data refers to the collection of data that cannot be captured, managed and processed by Changchang grinding gauge software tools within a certain time range, and it is a massive, high-growth rate and diversified information asset that requires a new processing mode to have stronger chain-breaking power, insight and process optimization capabilities.

First of all, what does data mean?

Human daily life, work, study and other behaviors are generating various types of data anytime and anywhere. For example, if you get up in the morning, go downstairs to the breakfast restaurant for breakfast, and then take the subway to work in the company, a lot of data is generated, such as your identity information, what time you get up, what facial cleanser you use to wash, what toothpaste, what time you arrive at the downstairs breakfast shop, what you eat for breakfast, how you paid for it, how much you paid, how far from the breakfast shop to the subway station, how to get there, what time you get to the subway station, how many lines you do, what web pages you use your mobile phone to browse on the subway, what time do you get off the subway, What time does it arrive at the company and so on. All that is pure and there is data is this.

Second, what does "big" mean by big data?

The "big" of big data does not mean that there is a large amount of data, but that all the data generated by human daily life, work and study behaviors are collected, processed, analyzed, and correlated, and on the basis of a large amount of data, a large correlation and connection are carried out, so as to play a large role.

Finally, what does big data mean, and how can the concept be understood?

1. Big data collects a large amount of data of various types in the process of human daily life, work, study and other behaviors.

2. Big data uses high-performance system software to process and analyze the collected data to find out the relationship between these data.

3. Big data correlates the processed data.

4. Big data identifies something that is happening and something that will happen in the future through the association of data.

5. Big data doesn't pay attention to why this happens.

6. Big data is analyzed through data association: what is the law of this thing? What will happen in the future?

Big data, an IT industry term, refers to a collection of data that cannot be captured, managed, and processed by conventional software tools within a certain time frame, and is a massive, high-growth and diversified information asset that requires new processing models to have stronger decision-making, insight and process optimization capabilities.

Some people have likened data to a coal mine with energy. Coal is classified according to its nature, such as coking coal, anthracite, fertile coal, lean coal, etc., while the excavation cost of open-pit coal mines and deep mountain coal mines is different. Similarly, big data is not "big", but "useful".

Value content and excavation cost are more important than quantity. For many industries, how to leverage this large-scale data is key to winning the competition.

The value of big data is reflected in the following aspects:

1) Enterprises that provide products or services to a large number of consumers can use big data for precision marketing;

2) Small and medium-sized micro enterprises with a small and beautiful model can use big data to do service transformation;

3) In the face of the pressure of the Internet, traditional enterprises that must transform need to keep pace with the times and make full use of the value of big data.

However, the great significance of "big data" in economic development does not mean that it can replace all rational thinking on social issues, and the logic of scientific development cannot be annihilated in massive data. The famous economist Ludwig von Mises once reminded: "Today, there are many people who are so busy with the useless accumulation of information that they lose their understanding of the special economic significance of explaining and solving problems."

This is indeed something to be wary of.

In this era of rapidly evolving smart hardware, one of the most important questions plaguing application developers is how to find that delicate balance between power, range, transfer rate, and cost. Organizations use data and analytics to help them reduce costs, increase efficiency, develop new products, make more informed business decisions, and more. For example, by combining big data and high-performance analytics, the following can be beneficial to the business:

1) Analyze the root cause of failures, problems, and defects in a timely manner, and the model sun can save the enterprise billions of dollars every year.

2) Plan real-time traffic routes for thousands of delivery vehicles to avoid congestion.

3) Analyze all SKUs, price and clear inventory with the goal of maximizing profits.

4) According to the customer's buying habits, push the preferential information that he may be interested in.

5) Quickly identify gold customers from a large number of customers.

6) Use clickstream analytics and data mining to circumvent fraud.

Practical application. Statistician Nate Silver uses big data to ** the results of the 2012 U.S. election.

The Massachusetts Institute of Technology (MIT) uses cell phone location data and traffic data to build urban planning.

Macy's real-time pricing mechanism. Based on demand and inventory, the company's SAS-based system adjusts prices for up to 73 million items in real time.

The medical industry has long encountered the challenge of massive data and unstructured data, and in recent years, many countries have been actively promoting the development of medical informatization, which has made many medical institutions in Zhongyan have funds to do big data analysis.

Big data technology refers to the ability to quickly obtain valuable information from a variety of massive types of slag-resistant data. Technologies for big data, including massively parallel processing (MPP) databases, data mining power grids, beam-cavity distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems.

Big data has the following four characteristics:

First, the amount of data is huge. For example, the amount of data for all Chang Di printed materials produced by humans is only 200 petabytes. The capacity of a typical personal computer hard drive is terabytes, while some large enterprises are already close to exabytes of data.

Second, there are various types of data. The current data type is not only in the form of text, but also in the form of **, **, audio, geolocation information and other types of data, and personalized data accounts for the absolute majority.

Third, the processing speed is fast. Data processing follows the "1-second rule", which allows for quick information on the best values from various types of data.