Big Data is the massive amount of data, generally at least to reach the TB level to be considered big data, compared to the traditional intra-enterprise data, big data content and structure to be more diverse, numerical values, text, video, voice, images, documents, XML, HTML, etc. can be used as the content of big data. When it comes to big data, the most common application is big data analysis, the data source of big data analysis 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: government, banking, national economy and people's livelihood, industry industry, social networking sites and other data, through the large amount of data through the big data analysis technology and tools for statistical summarization of the data, graphical charts of the data presentation, to achieve the data analysis. Through big data analysis technology and tools, the massive data will be summarized statistically and then presented in graphical charts to realize data visualization, and on this basis, combined with machine learning algorithms, the data will be mined in depth 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 industry and 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, medical care, energy, manufacturing, telecommunication industry and so on. 1. internet The application of big data in the industry represents the field of e-commerce, social networking, network retrieval, which can be based on sales data, customer behavior (activity, product preference, purchase rate, etc.) data, transaction data, product collection data, after-sales data, etc., search data portraying the user profile, according to the customer's preferences to recommend the corresponding products for them. 2. The government industry in the part of the big data analysis includes the quality inspection department, public security department, quality control department, meteorological department, medical department, etc., the quality control department, the medical department, the medical department, and so on, 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 meteorological changes, searches for the best solutions, and plans for emergencies and disaster relief by constructing the assessment model of the atmospheric movement pattern, correlation analysis of meteorological changes, and other paths. 3. Big data analytics in the financial industry is mostly applied to banking, securities, and securities industry. data analysis is mostly applied to banking, securities, insurance and other segments, in terms of big data analysis combined with a variety of channel data for analysis, customer behavioral data on social media, transaction data consumed on the website, customers for business reserved data, combined with the age of the customer, the size of the assets, consumption preferences, etc. to accurately locate the customer base, analyze their needs in the financial industry, etc. 4. Traditional industries include: Energy, Telecom, Real Estate, Retail, Manufacturing, etc. The telecom industry analyzes sensor data anomalies with the help of big data applications, predicts equipment failures, and improves user satisfaction; the energy industry uses big data analysis to tap into customer behavioral characteristics, consumption patterns, and improve the accuracy of energy demand; the real estate industry, through the mining and analysis of internal and external data, enables managers to grasp and understand potential market demand in the real estate industry, to master the business situation and dynamics, and to implement dynamic pricing and differential pricing for niche markets, etc.; the manufacturing industry includes. Real estate industry through internal and external data mining analysis, so that managers can grasp and understand the potential market demand in the real estate industry, understand the business situation and dynamics, and implement dynamic and differential pricing for market segments. Along 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.