FinTech Products

● Data asset operation platform-Galaxy ● Poor data management leads to unreliable data; Data management is not compliant and will be punished by the regulatory authorities; The sources of data generation are more and more complex, and it is more and more difficult to manage data. Data asset management can control the whole process of data generation, acquisition, processing, storage, transmission and application, making data more valuable. Inventory of data assets With the frequent occurrence of data leakage incidents, the awareness of data security is gradually established. However, when we put forward the demand of data security construction, we often don't know much about our own data assets, which will bring a problem. We don't know who to protect, how to protect? Therefore, to protect data security, we cannot simply and rudely implement security prevention and control measures directly on data assets. Before that, we must understand our data assets. In reality, the data assets of enterprises are often distributed in different departments, and the structure, distribution, quality and management of data in each department are different, and the data assets are often fragmented. Therefore, enterprises need to know and master which data assets they own, where they are distributed, who controls and uses them, and so on. In order to understand these, it is necessary to make an inventory of data assets. Data asset inventory is to sort out, standardize and uniformly classify the data assets in an enterprise, make them centralized and independent of the enterprise information system, and manage them according to certain norms, technologies and methods to maintain their consistency, integrity and effectiveness in the whole enterprise. The list of data assets will determine: What data assets does the enterprise own? Who owns and manages it? Who used which data assets? Where are the data assets stored? How do data assets flow in the system? After mastering the distribution of data assets, it needs to be further combed and summarized. Data asset inventory should take metadata as the core, identify, locate, evaluate and manage data assets from various angles such as classification, theme and application, and establish a panoramic view of data assets to popularize data asset discovery. Using the data asset catalog can make the fuzzy data assets in an organization clear, so that prospective users can spend less time looking for data and more time using data. Data asset evaluation is based on an objective, standardized, fair and feasible data asset evaluation system. According to different data sources and data types, data quality evaluation, data value evaluation and data asset alliance authentication are carried out to realize effective identification and reasonable evaluation of data assets and build a comprehensive data asset value evaluation system. In the data asset value management business, in order to enhance the value of data assets, it also includes data cleaning, desensitization of important data, metadata construction, authority control management, data integration, data summary and other data asset fusion analysis related contents. Galaxy data asset operation platform Galaxy data asset operation platform is dedicated to helping enterprises revitalize their data assets based on insight into the digital needs of many enterprises and rich experience in unified data management of large enterprises. Product Overview Galaxy Data Asset Operation Platform is based on DAMA (International Data Management Association) data management concept. In order to achieve the enterprise data strategy and planning objectives, a unified enterprise-level data management platform is established with metadata as the carrier and policies and systems related to data accountability and data governance as the guarantee mechanism, so as to realize the effective integration and interaction of data management topics such as metadata, data standards and data quality, assist in the development and promotion of various data management work, improve the application and service level of enterprise data, and promote the overall dataization of the enterprise. Product features and advantages There is no threshold to support the deployment on traditional OLTP database, MPP architecture database, memory database and Hadoop big data platform. Security compliance: A variety of desensitization schemes can be selected to ensure data security and privacy security, and flexible and extensible management modules and functional components. Customers can integrate big data quality verification technology as needed. The application of big data technology and distributed technology such as Storm and Spark greatly improves the verification efficiency, far exceeding the efficiency of traditional similar products. One-stop management integrates metadata, data standards, data quality and other functional modules to help enterprise data governance. The value brought to customers creates an enterprise-wide data governance atmosphere, enhances the importance of the whole enterprise, strengthens the awareness of using numbers, and creates a good atmosphere of "promoting use with governance and combining with governance". At the same time, it reduces the complexity of data governance, provides a unified data standard, improves the ability of data reuse and sharing, reduces the work of data cleaning, and promotes the automation of the process. According to the guidance of external regulatory standards, respond to regulatory requirements, guide the formulation and implementation of enterprise standards, improve the quality of enterprise data, and meet the requirements of regulatory agencies. Capitalization of data resources can improve the quality of data by integrating and cleaning up the data that was difficult to use in the past, so that it can reflect its value legally and justly. Continuously improve data quality. Establish a standard process of data collection, data change and data maintenance for data development and management, and provide data quality monitoring on this basis to continuously improve data quality. Improve the operational efficiency of enterprises. Platform and visualize data assets to reduce data research and acquisition time in scenarios such as product and service innovation, risk management, business decision-making and refined management. As the carrier of digital transformation, Galaxy data assets are playing a role in all aspects of social production process. Digital transformation has had a subversive impact on the traditional data management and operation concept of the banking industry and even the data application model. What core data asset management and operation capabilities should banks have to provide a strong guarantee and foundation for data empowerment business and data value? The successful cases of cooperation between Galaxy Data Asset Operation Platform and China Postal Savings Bank, Nanjing Bank and Shanghai Bank have accelerated the evolution of banking financial technology to digitalization, intelligence and service.