Deepening the application of enterprise big data, NetEase's full-link big data product outlook

Digital transformation and upgrading are in the spotlight. Many companies regard data and resources as core assets, hoping to reduce costs and increase efficiency through data analysis and mining, and to gain greater development space by supporting business with data products. In fact, big data is also the foundation for building future intelligent enterprises. If artificial intelligence applications are brilliant sword moves, then the ability of big data is the internal strength required to launch the ultimate move. How to cultivate profound big data internal strength and maintain the company's competitive advantage is a big question that corporate managers must answer. This is also a core question to be answered at the NetEase Cloud Innovation Summit held in Hangzhou on July 26.

By visiting the NetEase Big Data team, the editor learned that NetEase Big Data believes that this problem can be easily solved by using full-link big data products to quickly build enterprise data middle-end capabilities, form unified data and services, and strongly support front-end business.

Enterprise big data practice enters deep waters

In 2012, "beer and diapers" is no longer a new thing. Researchers have even successfully used data analysis to "take pictures" of mysterious black holes. From the perspective of the integration of industry and big data technology, big data practices in various industries have entered the "deep water zone": Shulian Technology has successfully saved 80% of data analysis time and effectively improved the efficiency of the logistics supply chain by building an agile BI platform with the help of NetEase Youshu; Zhejiang Daily Group has adopted NetEase's big data technology to build a media hub platform, establish an intelligent and integrated information service system, and implement "data-driven communication and intelligent reconstruction of the media"; Jiangsu Rural Credit Cooperatives has cooperated with NetEase big data to build a "wall" that can be displayed, realizing the visualization of financial big data operation and maintenance; Wen's shares have introduced NetEase big data to build a "smart eye platform" to provide data monitoring, early warning, and decision-making support for daily operations and management, and enhance the technological content and corporate competitiveness of modern agricultural enterprises...

The practices of leading companies have stimulated more companies to accelerate the process of digital innovation. To paraphrase a familiar saying, companies are no longer thinking about whether to use big data, but how to use big data well.

Big data applications face challenges

Companies that have pioneered big data have overcome many difficulties and achieved current phased results. However, given the late start of information technology in my country, the large gap in high-end talent, and the uneven development of industries and regions, more companies are still struggling in the application of big data and face huge challenges.

Based on the experience of NetEase's big data team, the five major challenges of inconsistent indicators, repeated data construction, low data acquisition efficiency, frequent data product failures, and exponential cost growth are like a mountain of five elements pressing on the data team of the enterprise, and the enterprise is in urgent need of solutions. Even large group companies with strong information technology teams cannot avoid these problems due to historical reasons.

In 2018, the NetEase Big Data team successfully supported 231 large-scale projects and served more than 100,000 big data users. They have come into contact with a wide variety of teams, understood a variety of needs, encountered endless problems, and witnessed ever-changing scenarios. Their understanding of the implementation of big data in enterprises is deep-rooted.

NetEase's full-link big data product breaks through

As one of the core supports for NetEase's business development, NetEase's big data team has been committed to seeking ways to move the "Five Elements Mountain" and has successfully explored a set of solutions that have been verified in production environments. It has been applied to NetEase Yanxuan, Koala, Cloud Music and other businesses.

NetEase Big Data believes that solving the above problems requires a full-link solution covering enterprise business, including big data platform, data integration, data modeling, data governance related platforms and tools, and data standard system construction methodology, which is a complete data middle platform. Through this data middle platform, enterprises can build a unified, secure, and shared enterprise data asset system, realize the dataization of all businesses, connect data islands, drive all data businessization, help digital transformation, and make data generate value.

Based on this understanding, the NetEase big data team has created a full-link big data product covering indicator systems, data maps, full-link monitoring, data asset management, etc., and released it at the NetEase Cloud Innovation Summit to support the construction of enterprise data middle platforms and provide unified data and services for enterprise applications.

One of the goals of the NetEase Cloud Innovation Summit is to help practitioners who are committed to clearing the "Five Elements Mountain" of big data applications to jointly analyze the crux and explore the most optimized solutions. Therefore, the Cloud Innovation Summit also set up the NetEase Big Data Forum, providing a platform for enterprises from different industries to discuss the continuous optimization of data middle-end platform tools and methodologies, so that they can adapt to the needs of more scenarios and play a greater role in the digital upgrade of Chinese enterprises.

If you are confused about enterprise big data applications, or are eager to learn about cutting-edge big data practices, please log in to the official website of the Cloud Innovation Summit to register in advance.