Big data is the massive amount of data, generally at least to reach the terabyte level to be considered big data, compared to the traditional intra-enterprise data, the content and structure of big data to be more diverse, numerical values, text, video, voice, images, documents, XML, HTML, etc. can be used as the content of big data.
Mention of big data, the most common application is big data analysis, big data analysis of the data source is not only limited to the enterprise internal information system, but also includes a variety of external systems, machines and equipment, sensors, database data, such as: the government, banks, the national economy and people's livelihood, the industry industry, social networking sites, and other data, through the large amount of data through the big data analysis technology and tools for statistical summaries The data will be displayed in graphical charts to visualize the data, and on this basis, combined with machine learning algorithms, the data will be y mined to explore the potential value of the data.
Application part, big data not only includes data analysis of internal application systems, but also includes the deep integration with the industry, industry, big data analysis application scenarios with industry, different industries present different content and analysis dimensions, specific scenarios include: the Internet industry, the government industry, the financial industry, the real estate of traditional enterprises, health care, energy, manufacturing, telecommunication industry and so on.
1. The application of big data in the Internet industry represents the field of e-commerce, social networking, and network retrieval, which can be used to portray user profiles based on sales data, customer behavior (activity, product preference, purchase rate, etc.) data, transaction data, product collection data, after-sales data, etc., and search data, and to recommend the corresponding products for customers based on their preferences.
2. The governmental industry in the big data analysis part includes quality inspection department, public security department, meteorological department, medical department, etc. The quality inspection department includes collecting, verifying, and checking the information of the whole process of commodity production, processing, logistics, trade, and consumption, to ensure the safety of food items; the meteorological department accurately predicts the meteorological changes by constructing the evaluation model of the laws of atmospheric movement, and the paths of meteorological changes correlation analysis, to find the best solutions and find the best solutions. meteorological changes, find the best solutions, and plan emergency and disaster relief work.
3. Big data analysis in the financial industry is mostly applied to banking, securities, insurance and other segments, in terms of big data analysis combined with a variety of channel data to analyze the customer's behavioral data on social media, the transaction data consumed on the website, and the reserved data of the customer's handling of the business, and combined with the customer's age, asset size, and consumption preferences, etc., to accurately locate the customer base and analyze their needs of the financial industry, etc.
4. Traditional industries include: energy, telecommunications, real estate, retail, manufacturing and so on. Telecommunications industry with the help of big data applications to analyze sensor data anomalies, predict equipment failures, improve user satisfaction; energy industry using big data analysis to dig customer behavior characteristics, consumption patterns, improve the accuracy of energy demand; real estate industry through internal and external data mining analysis, so that managers grasp and understand the potential market demand of the real estate industry, to master the business situation and dynamics of the implementation of the dynamic market segments, pricing and differential pricing; manufacturing industry through the mining analysis, so that managers grasp and understand the potential market demand, master business situation and dynamics of the implementation of dynamic The real estate industry, through internal and external data mining and analysis, enables managers to grasp and understand the potential market demand in the real estate industry, grasp the business situation and dynamics, and implement dynamic and differential pricing for market segments.
With the rapid development of information technology, data volume increased, has entered the data era, I believe that the application of big data between the industries will be more and more in-depth.