On May 16, the 2023 International Asset Management Technology Entrepreneurs and Investors Conference "Asset Management Data Processing (Large Model) Technology" session was held in Shanghai. With the theme of "Asset Management Digital Intelligence Technology", this conference invites enterprises, universities, investment institutions and other parties to carry out industrial exchanges and discussions, and share and create opportunities for the industry.
Kuker Data was invited to participate in the meeting as a leading company in the cloud-native data warehouse in China. Vice President Wei Yi shared new ideas, new technologies, and new practices in the combination of big data and the asset management industry at the meeting.
Wei Yi said that HashData cloud data warehouse is the most suitable data analysis platform solution for the characteristics of rich data sources, high proportion of unstructured data, and wide distribution of institutions in the asset management industry. Based on the cloud-native architecture, through the mature practice of "separation of storage and computing" and "integration of lake and warehouse", HashData can eliminate "data islands", integrate internal and external data sources, flexibly manage and analyze unstructured data, and realize global data sharing and efficient access , providing asset management companies with cross-regional and cross-departmental data resource management, flexible supply, multi-site and multi-active deployment capabilities, enabling asset management companies to fully release the value of data resources and gain development opportunities.
Opportunities and challenges of data management in the financial industry in the era of big data
Data warehouse is an important infrastructure of the financial industry and plays a vital role in the process of data value mining.
Wei Yi said that the financial industry is information- and data-intensive and has extremely stringent requirements for data warehouses. In the past, the financial industry usually used MPP products integrating deposit and calculation to build data warehouses. However, with the advancement of financial technology and the surge in data volume, challenges such as high concurrency, massive data, and ultra-high peaks have come one after another, resulting in a substantial increase in the demand for data resource storage, computing, and applications.
In recent years, the financial industry is facing online, paperless, and scenario-based digital reforms. The application scenarios are complex and the data scale is increasing. The traditional data warehouse cannot cope with the elastic expansion brought about by the business tide and cannot satisfy tens of millions of queries per day. and million-table-level complex queries. At the same time, the lack of multi-AZ deployment and cross-site disaster recovery solutions in traditional data warehouses has become a constraint in the digital transformation of financial enterprises.
Faced with the challenges brought by traditional data warehouses, many consulting agencies have proposed diversified and hybrid architecture ideas, and technically introduced pure soft MPP databases and Hadoop. However, as financial business loads become more and more complex and demand increases, the defects of diversified platforms that cannot achieve high concurrency and load isolation become more and more prominent, making it difficult to meet the requirements of elasticity, high concurrency, and high reliability. At the same time, there are still business experience Fluctuations, insufficient data integration, poor data support, complex operation and maintenance management and other shortcomings.
Wei Yi pointed out that in the era of big data + cloud computing, the financial industry urgently needs a next-generation data warehouse platform that can adapt to business elastic changes and provide a good analysis experience, so as to provide technical support for the innovative development of financial enterprises.
Wei Yi believes that a modern financial enterprise data analysis platform must have multi-form data management capabilities, diversified analysis and computing capabilities, and multi-dimensional elastic scalability capabilities, and at the same time be compatible with structured, semi-structured, unstructured and other different forms and different timeliness Perform diversified calculations and analyzes on permanent data, and perform elastic scaling according to changes in business requirements.
Cloud computing technology can well address the above-mentioned needs, and mainstream public cloud vendors at home and abroad have also launched database products based on cloud-native architecture. At the same time, independent software vendors such as Snowflake and Databricks have also launched products that separate storage and computing, and integrate lakes and warehouses.
Since its birth, the cloud-native data warehouse has rapidly developed into the mainstream trend of the industry. According to reports released by several market research institutions, the market share of cloud-native data warehouses will surpass that of traditional data warehouses. Gartner predicts that 75% of the world's databases will run on the cloud in the future.
HashData helps the financial industry improve quality and efficiency
At present, the digital economy has become an important engine for my country's economic development. For financial institutions, data has also become the core resource throughout the digital transformation of the financial industry.
With the transition from financial informatization to digitalization, the supporting capacity of the database determines the success or failure of the digital transformation of financial institutions to a certain extent.
Compared with databases with traditional MPP architecture, cloud-native data warehouses have significantly improved the efficiency of enterprise data analysis.
According to a survey of four companies using Snowflake by the independent consulting firm Forresters, the cumulative value created in three years exceeded 21 million US dollars, and the ROI equivalent reached 612%. Among them, the data operation cost was saved by 2.11 million US dollars, and the database and infrastructure operation cost was saved by 5.95 million US dollars. At the same time, Snowflake can drastically reduce computing time, increase profits, and provide better decision-making based on data.
As the first independent software vendor in China to focus on the research and development of cloud-native data warehouses, HashData has been practicing the concept of "cloud-native" since its establishment in 2016, and is committed to building a world-class cloud-native data warehouse.
HashData cloud data warehouse adopts the industry-leading cloud-native big data system design concept represented by Snowflake, Databricks and Google BigQuery, and is built around object storage and abstract services. Through the separation of metadata, computing and storage, multiple clusters share and unify The structure of the data storage layer maximizes the advantages of cloud computing, and utilizes the characteristics of elasticity and distribution of the cloud platform to achieve rapid deployment, on-demand scaling, non-stop delivery, etc., which greatly reduces the threshold for enterprises to conduct big data analysis.
As an enterprise-level cloud-native data warehouse, HashData provides high concurrency, elasticity, ease of use, high availability, high performance, and scalability unmatched by traditional solutions through innovative storage, computing, service, and application layer architecture designs. With the characteristics of cloud-native, loosely coupled applications, integration of lakes and warehouses, and almost "zero operation and maintenance", it can meet the all-round needs of customers with high security, high reliability, high scalability, and intelligence, and provide financial institutions with comprehensive functions, stable and reliable, An enterprise-level database service with strong scalability and superior performance.
Over the years, HashData has continued to cultivate core financial scenarios and accumulated rich practical experience. At present, HashData has achieved large-scale commercial implementation in many large state-owned banks, joint-stock banks, top brokerages and other institutions, and supported the world's largest single customer cluster in the financial industry.
Taking Hengfeng Bank as an example, by introducing the "perseverance system" built by HashData cloud data warehouse, it successfully solved the waste of resources, poor scalability, small concurrent support, inability to quickly expand and shrink, data islands, data redundancy, etc. Operation and maintenance workload and other issues.
Compared with the old system, the Perseverance system has achieved multi-faceted capacity improvements, with core processing capacity increased by 6.38 times, card business transaction processing capacity per second increased by 23.8 times, and online payment business transaction processing capacity per second increased by 17.7 times. At the same time, the "Perseverance System" saves about 30% of server costs while meeting the needs of the industry to plan new data warehouses to support application computing services.
Wei Yi said that in the future, HashData will continue to build comprehensive financial digital capabilities, and build a "digital base" for financial transformation and innovative development through in-depth solutions and service capabilities for enterprise business scenarios, promote the implementation of financial digital strategies, and help Shanghai build a financial Technology Center and Global Asset Management Center.