What is financial data? What is financial big data?

What is financial data? Financial data refers to the financial industry.

The market data, company data, industry index and pricing data involved are collectively referred to, and all relevant data related to the financial industry can be classified as financial markets.

In the big data system, it provides a reference for practitioners to conduct market analysis.

Refinitiv (formerly Thomson Reuters.

The financial data provided by the financial and risk business segment can cover all major financial markets (including **, fixed income, commodities and foreign exchange, etc.), helping users find reasonable and effective data from the massive data, and judge the expected development and value of the market.

Financial data refers to the market data, company data, industry index and pricing data involved in the financial industry.

It refers to the market data, company data, industry index and pricing data involved in the financial industry, and all relevant data related to the financial industry can be classified into the financial market big data system. Based on the financial data provided by Refinitiv (formerly known as Thomson Reuters' Finance & Risk business unit), it can cover all major financial markets (including **, fixed income, commodities and foreign exchange, etc.), helping users find reasonable and effective data from the massive data, and judge the expected development and value of the market.

Big data finance refers to the collection of massive unstructured data, through real-time analysis, can provide Internet financial institutions with a full range of customer information, through the analysis and mining of customer transaction and consumption information to grasp the customer's consumption habits, and accurate customer behavior, so that financial institutions and financial service platforms in marketing and risk control targeted.

The content of big data finance: The financial service platform based on big data mainly refers to the financial services carried out by e-commerce enterprises with massive data. The key to big data is the ability to quickly obtain useful information from a large amount of data, or the ability to quickly monetize from big data assets, so the information processing of big data is often based on cloud computing.

Financial big data refers to the collection of massive unstructured data, analysis and mining of customer transaction and consumption information, grasp the consumption habits of customers, accurately improve customer behavior, and improve the service, marketing and risk control capabilities of financial institutions.

1. Big data finance is mainly reflected in three aspects: first, objective and accurate matching of data; Second, the transaction cost is low and the customer base is large; Finally, the data is timely and effective, which helps to control risk.

2. Big data finance collects data such as customer transaction information, community communication behavior, and capital flow trends through big data technology. Big data finance understands the consumption habits of customers, launches different marketing and advertisements for different customers, or analyzes the credit status of customers.

Extended information: 1) Because big data financial data is collected based on the customer's own behavior, big data finance is objective and true. Therefore, the resale plan and preference recommendation formulated by big data finance for customers can also be accurate, and the big data finance has a high degree of matching.

Big data finance is based on cloud computing technology Cloud computing is a kind of ultra-large-scale distributed computing technology, through preset programs, big data financial cloud computing can search, calculate and analyze all kinds of customer data without manual participation.

2) Big data financial cloud computing technology reduces the cost of collecting and analyzing data, not only integrates fragmented needs and innovation, but also greatly reduces the cost of big data financial transactions, realizes cross-regional information flow and exchange, and grows the customer base. In the big data financial model, Internet companies set various risk indicators, such as default rate, late delivery rate, after-sales complaint rate, etc., and the customer data collected by big data finance is real-time, because its credit evaluation is also real-time. Time is conducive to the data demander to analyze the credit status of the other party in a timely manner, and control and prevent transaction risks.

3) Big data, or massive data, refers to the massive amount of data involved, which cannot be retrieved, managed, processed and organized into information through mainstream software tools, helping enterprises make more positive business decisions in a reasonable time. Gartner, the "Big Data" research institute, gives such a definition. "Big data" requires a new processing paradigm with stronger decision-making, insight and discovery, and process optimization capabilities to adapt to massive, high-growth and diverse information assets.

Financial data refers to market data, company data, industry indices, and pricing data involved in the financial industry. All data related to the financial industry can be incorporated into the financial market big data system to provide reference for practitioners to conduct market analysis. There are many academic definitions, and for example, a certain **period** data arranged in a given time order can be called a kind of financial time series data.

Based on the financial data provided by LOFT (formerly Thomson Reuters Finance & Risk Business Unit), it can cover all major financial markets (including**, fixed income, commodities and foreign exchange) to help users find reasonable and effective data Judging the expected development and value of the market from the massive data. Financial data processing refers to the process of processing the collected data into data that meets the requirements of the purpose through certain means and in accordance with certain procedures and requirements. In addition to the general characteristics of data, financial data has its own characteristics:

universality, comprehensiveness, reliability and continuity; The particularity of financial data makes the processing of financial data have its own special places and special requirements. It has stricter input auditing, greater storage capacity, wider network transmission, and more frequent data maintenance.

Purpose of financial data:

1) Convert the data into a form that is convenient for observation and analysis, easy to transmit or convenient for further processing;

2) processing the data into new data that is conducive to decision-making;

3) Store the data for later use.

Extended information: In order for data to truly reflect the attributes of objective things, two conditions must be met:

First, it must belong to the individual and be a reflection of the individual's attributes; Second, data, as a record of object attributes, must have a certain physical carrier. Financial data refers to the data generated in various financial activities. Finance is an important part of the national economy and is closely related to all walks of life in the national economy.

Second, the financial industry is actually providing a full range of services for the whole society by carrying out financial activities and doing a good job in its own operations. Therefore, the data generated in financial activities is not only an objective description of the business activities of financial institutions, but also a comprehensive reflection of the macro and micro conditions of the national economy, which makes financial data and financial data processing have some characteristics of their own.

The so-called big data finance is the use of big data technology to carry out financial services, that is, the collection of large-scale structured, semi-structured, unstructured data, real-time analysis through the Internet, cloud computing and data mining and other information processing, to provide customers with a full range of information, and through the analysis and mining of customer transactions and customer consumption habits of information, customer behavior, in order to combine traditional financial services, financial integration, innovative financial services.

1. First of all, we must understand various financial terms and some financial concepts, which is the first step to understand financial data and financial technology;

2. It is necessary to systematically understand the structure of financial knowledge;

3. The relationship between the various items in each header of the ** should be clarified, so as to facilitate the subsequent analysis;

4. The trend of data change can be studied.

It is also necessary to learn accounting, preferably management accounting, to be able to distinguish the real data in the statements.

Learn financial knowledge systematically.

First of all, you must be sensitive to numbers, and then you can pay attention to the ** index every day, learn to do some analysis by yourself, and secondly, economics should also be able to calculate...

First of all, through big data, you can analyze the customer's personal information, income, risk appetite, etc., and you can recommend the corresponding financial products, if which age groups and working groups are suitable**, insurance and other valuable**;

Secondly, in the development of financial products, there are mainly insurance products and some other products, through the incidence rate, disaster probability, etc., actuarial calculations, the development of insurance products, some other new financial products will also involve data analysis;

Again, in the pricing and investment analysis of financial products, many factors will affect financial products, such as **, **, spot, etc., through data mining, find out their influencing factors, and conduct ** analysis.

Big data and data mining mainly have these applications, of course, there are other aspects, and there are many books on finance and data analysis, which can be further studied and hopefully adopted.