What is the meaning of big data?

What is big data and what does it mean?

Big data means that data should be online, so that your data can be valuable for analysis or processing. It is meaningful to analyze a large amount of data online. You may get the data you want, many of which are used in movies, such as face search, personnel positioning, traffic analysis, running status and so on. There are many applications now, but less landing. Or create value.

What is big data, why it is important, and how to apply it.

Talking about data doesn't make much sense. It depends on the main direction of the data. 1. From the technical application direction, our data is mainly used for communication guidance; 2. In the process of data research, our data mainly comes from the public data on the Internet (media data, self-media data, enterprise self-operated media data), which solves the problems of user insight, communication effect, competitive intelligence acquisition and so on. 3. We mainly study the dimensions of big data. Our dimensions are more and wider, and the number of dimensions determines the effect.

The meaning of big data

Today's society is a rapidly developing society with advanced technology and information circulation. People's communication is getting closer and closer, and life is becoming more and more convenient. Big data is the product of this high-tech era. Ma Yun, founder of Alibaba, mentioned in his speech that the future era will not be the IT era, but the DT era. DT is Data Technology, and showing big data is very important for Alibaba Group. Some people compare the data to a coal mine with energy. Coal is divided into coking coal, anthracite, fat coal and lean coal by nature, but the mining cost of open-pit coal mine and deep-mountain coal mine is different. Similarly, big data is not "big" but "useful". Value content and mining cost are more important than quantity. For many industries, how to use these large-scale data is the key to win 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 precise marketing; 2) Small and beautiful long-tail enterprises can use big data for service transformation; 3) Traditional enterprises that must be transformed under the pressure of the Internet 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. Ludwig von mises, a famous economist, once warned: "As far as today is concerned, many people are so busy accumulating useless information that they lose their understanding of the special economic significance of explaining and solving problems." This really requires vigilance. In this era of rapid development of intelligent hardware, an important problem that puzzles application developers is how to find that delicate balance among power consumption, coverage, transmission rate and cost. Enterprises can use relevant data and analysis to help them reduce costs, improve efficiency, develop new products, make more informed business decisions and so on. For example, combining big data with high-performance analysis may lead to the following beneficial situations for enterprises: 1) Analyzing the root causes of faults, problems and defects in time may save enterprises billions of dollars every year. 2) Plan real-time traffic routes for thousands of express vehicles to avoid congestion. 3) To maximize profits, analyze all SKUs, prices and clear inventory. 4) Push the preferential information that the customer may be interested in according to his buying habits. 5) Quickly identify gold medal customers from a large number of customers. 6) Use clickstream analysis and data mining to avoid fraud.

What is big data, why it is important, and how to apply it.

Read this book. .

Harnessing Big Data and Harnessing the Future

The popularity of big data has also triggered the warming of the publishing theme of big data in the book industry. Last year's Big Data (by Tu Zipei) described American management in a simple way from the perspective of data governance, and explained the essence of Mr. Huang Renyu's "capitalist numerical management" in detail. Recently, People's Posts and Telecommunications Publishing House organized the translation and publication of the book "Harnessing Big Data" by Bill Franks of the United States.

The overall idea of the book, in short, is to describe a process of "data collection-knowledge formation-intelligent action", which not only answers "what", but also points out "how", providing specific technologies, processes and methods, and even team building and cultural innovation. The first chapter analyzes the rise of big data, introduces the concept, content and value of big data, analyzes the source of big data, and discusses the application scenarios of big data in automobile insurance, electric power and retail industries. The second chapter introduces the technology, process and method of controlling big data. The third part introduces the capability framework of controlling big data, including how to conduct high-quality analysis, how to become an excellent analyst and how to build a high-performance team. Finally, the significance of enterprise innovation culture is put forward. The book is strategically located, and its content is wanton, but Wang Yang is hearty. It is a rare book with complete system, rich content, unique knowledge and strong practicability.

Important and unimportant aspects of big data

Different from what most people take for granted, the author thinks that "big" and "data" in "big data" are not important. What matters is the value that data can bring and how to control these big data. Even different from traditional structured data and textbooks, "big data may be messy and ugly" will also bring "being overwhelmed by big data and thus stopping" and "the cost growth rate of big data processing". When dealing with data, the author points out that "a lot of big data is actually not important". The key for enterprises to do big data well is how to find gold in the sand, combine or mix and match with various data, and explore its value. This is why the author has repeatedly stressed that "new data will surpass new tools and methods every time".

Network data and e-commerce

Mining customer behavior is no longer a hot concept. However, the author thinks that from a deeper level, the analysis of customer's intention and decision-making process is a valuable gold mine, that is, "what is the idea of buying goods and what are the key factors affecting their purchase decision?" For the data mining of customer behavior such as e-commerce, the author is not general, but insightful, and provides very attractive suggestions from the aspects of purchase path, preference, behavior, feedback, loss model, response model, customer classification, advertising effect evaluation and so on. I think that the network data proposed by the author of "Harnessing Big Data" as the "raw data" of big data actually contains another meaning, that is, only e-commerce can interact deeply with customers, and it also has the conditions to collect these data. From this perspective, it is not ridiculous for enterprises directly facing the terminal to talk about big data without talking about electricity. Of course, this behavior analysis of users' purchase path is not new. Underhill disclosed in the book Why Customers Buy: The Bible of Retail Industry in the New Era that shopping malls employ a large number of consultants to secretly follow customers, and use cameras or cards filled with secret words to completely and truly record every movement of customers from entering to leaving the shopping mall, and make in-depth summary and analysis, so as to improve the display position of goods, the wording of advertisements and the place to put them. Both of them are similar to the customer behavior mining in the e-commerce era. Of course, in the era of e-commerce, the cost of data analysis is lower, and it is easier to obtain data that can be collected through indirect observation (such as credit records).

Some valuable application scenarios

The value of big data can only be reflected through some specific application modes and scenarios. E-commerce is a case. At the same time, the author also mentioned that in-vehicle information "originally appeared as a tool to help car owners and companies obtain better and more effective vehicle insurance". However, the information it can provide, such as speed, road section, start and end time, has unexpected value for improving urban traffic congestion. Based on GPS technology and hand ......

What does the arrival of big data mean to China's economic development?

Big data refers to data that traditional software tools can't capture, manage and process within an affordable time range.

Some people compare the data to a coal mine with energy. Coal is divided into coking coal, anthracite, fat coal and lean coal by nature, but the mining cost of open-pit coal mine and deep-mountain coal mine is different. Similarly, big data is not "big" but "useful". Value content and mining cost are more important than quantity. For many industries, how to use these large-scale data is the key to win 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 precise marketing;

2) Medium-and long-tail enterprises that make small and beautiful models can use big data for service transformation;

3) Traditional enterprises that must be transformed under the pressure of the Internet need to keep pace with the times and make full use of the value of big data.

What are the benefits of big data on the Internet?

What is big data? Why use big data? What are the popular big data tools? This article will answer for you.

Now, big data is a popular word that is abused, but its real value can be realized even by a small enterprise.

By integrating data from different sources, such as network analysis, social data, users and local data, big data can help you understand the overall situation. Big data analysis is getting easier and cheaper, and it is easier to accelerate the understanding of business than before.

Big data usually has the same characteristics as business intelligence (BI) and data warehouse: high cost, high difficulty and high risk.

Previous business intelligence and data warehouse plans failed because they spent months or even years obtaining quantifiable benefits for shareholders. However, this is not the case. In fact, you can get your real intention on the same day, at least in a few weeks.

Why use big data?

The data is growing at an explosive rate. A notable example comes from our customers, who mostly use Google Analytics. When they analyze data for a long time or use advanced segmentation, the data analyzed by Google begins to be sampled, which will hide the true value of the data.

Now our tool Clickstreamr can collect a lot of click-level data, so you can track every click behavior of users in their access path (or access stream). In addition, if you add some other data sources, it will really become big data.

A more comprehensive analysis

Big data Big data is not just a lot of data. His real significance lies in completing a more complete report according to the relevant data background. For example, if you add your CRM data to the data analysis of your website, you may find a high-value user group that you have long known. They are women, living on the west coast, aged between 30 and 45, and spend a lot of time on Pinterest and Facebook.

Now that you have this knowledge, that is how to effectively build and acquire more high-value users.

Companies like Tableau and Google have brought users more powerful data analysis tools (such as big data analysis). Tableau provides a visual analysis software solution with an annual price of $2,000. Google provides the BigQuery tool, which allows you to analyze your data in a few minutes to meet any budget requirements.

What is big data?

Because big data is usually mixed structure, semi-structured and unstructured data, it is difficult to associate, process and manage big data, especially with traditional relational databases. When it comes to big data, analysts of Gartner Group (founded in 1979, the first information technology research and analysis company) divide it into three V's:

Volume: a lot of data

Speed: high-speed data output.

Diversity: data of various types and sources.

As we said, most enterprises are generating a large amount of data in different fields every day. The following are a set of sample data sources and types, which are all potential ways for enterprises to collect and aggregate data when conducting big data analysis:

Network analysis

Mobile analysis

Device/sensor data

User data (CRM)

Unified enterprise data (ERP)

Social data

accounting system

Point of sale system

Sales system

Consumer data (for example, data from eBay, data from the Deng's Business Association or census data)

Company internal spreadsheet

Company internal database

Location data (spatial location, GPS location)

climatological data

But don't do too much for unlimited data sources. Pay attention to relevant data and start with small data. It is usually a good suggestion to start with 2-3 data sources, such as website data, consumer data and CRM, which will give you some valuable insights. After you enter big data analysis for the first time, you can start adding data sources to promote your analysis and publish more analysis results.

If you want to know more details about big data, you can go to the big data portal of * * *.

Advantages of big data

Big data provides a forward-looking way to identify and take advantage of high-value opportunities. If you like, big data can provide things like ......

What does "big data" really mean?

Bigdata online training on the big platform will answer your question: Big data refers to data that can't be captured, managed and processed by conventional software tools in a certain period of time. It is a massive, high-growth and diversified information asset, which needs a new processing mode to have stronger decision-making power, insight and discovery ability and process optimization ability. Technically, the relationship between big data and cloud computing is as inseparable as the front and back of a coin. Big data cannot be processed by a single computer, and it must adopt a distributed architecture. It is characterized by distributed data mining of massive data. But it must rely on the distributed processing of cloud computing, distributed database, cloud storage and virtualization technology. Big data requires special technology to effectively process a large amount of data within the allowed time. Technologies suitable for big data include MPP database, data mining, distributed file system, distributed database, cloud computing platform, Internet and extensible storage system.

The smallest basic unit is bit, and all units are given in order: bit, byte, KB, MB, GB, TB, PB, EB, ZB, YB, BB, NB and DB.

The benefits of big data to people

It is of little significance to ordinary users. It is also necessary for pharmacies and pharmaceutical companies to understand the needs of users, but it is still very useful if it is really used to bring convenience to users in drug selection. For example, when you are sick and don't know which medicine to choose, it can help you find the right medicine according to the principle of evidence-based medicine, which is also beneficial.

What does industrial big data mean for China?

Industrial big data can promote the application of big data in the whole life cycle of industrial R&D design, manufacturing, operation management, marketing, after-sales service and other products and the whole process of industrial chain, analyze and perceive user needs, enhance the added value of products, build smart factories, and promote the change of manufacturing mode and industrial transformation and upgrading.

In the next step, the country will use big data to promote the deep integration of informatization and industrialization, research and promote the application of big data in R&D, design and manufacturing, operation and management, marketing and after-sales service, research and develop big data analysis application platforms for different industries and different links, select typical enterprises, key industries and key regions to carry out pilot projects of big data application in industrial enterprises, and actively promote the networking and intelligence of manufacturing. In the process of application project pilot, it is necessary to evaluate the safety and reliability of application demonstration, and use big data testing technology, industrial electronic system testing technology and industrial cloud testing technology to ensure the steady progress of industrial enterprise big data application project pilot. China Software Evaluation Center has profound technical accumulation and case accumulation in related fields, which can escort the development of industrial big data in China.

What are the main characteristics of big data?

Big data refers to data captured, managed and processed by traditional software tools within an affordable time range.

Characteristics of big data:

1. volume: the size of the data determines the value and potential information of the considered data;

2. Diversity: the diversity of data types;

3. Speed: refers to the speed of obtaining data;

4. Variability: It hinders the process of effectively processing and managing data.

5. Authenticity: the quality of data.

6. Complexity: the amount of data is huge and the sources are multi-channel.

The meaning of big data:

Today's society is a rapidly developing society with advanced technology and information circulation. People's communication is getting closer and closer, and life is becoming more and more convenient. Big data is the product of this high-tech era.

Some people compare the data to a coal mine with energy. Coal is divided into coking coal, anthracite, fat coal and lean coal by nature, but the mining cost of open-pit coal mine and deep-mountain coal mine is different. Similarly, big data is not "big" but "useful". Value content and mining cost are more important than quantity. For many industries, how to use these large-scale data is the key to win the competition.

Defects 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 lost in massive data. Ludwig von mises, a famous economist, once warned: "As far as today is concerned, many people are so busy accumulating useless information that they lose their understanding of the special economic significance of explaining and solving problems." This really requires vigilance.