"Practice long-termism and always do what is meaningful to our customers"
"With a three-year limit, I think what needs to be solved urgently in the future data intelligence track is how to express the most valuable activities of customers with data and precipitate data assets."
Wen | Nie Kai
"He is strong, and the breeze blows on the hill." He crosses the river, and the bright moon shines on the river." All along, entrepreneurship is to place the growth of the self in a longer-term time dimension to make choices, adhere to long-termism, and reduce the influence from the outside world.
Dipu Technology believes that in the era of data intelligence, the enterprise service market is paying more and more attention to the value of customer data. How to fully empower the business through intelligent means and transform data into new production factors of enterprises has become an important factor in winning the second half of digital transformation of enterprises.
Therefore, the value capability of data is the core. Although Dip Technology was only established for three years, it is a veteran of the ToB circle.
Focusing on the future, how can Dipu Technology seize the opportunity, adhere to the long-term strategy, and continue to create value for customers?
When digital transformation enters the deep waters
Nowadays, with the continuous emergence of new technologies and new business scenarios, solving local efficiency problems is no longer the core demand of digital transformation, and has evolved from improving the efficiency of a single business process to connecting the data of all business links online, changing data from "consumables" to "assets", and then releasing data potential.
"With a limit of three years, I think what needs to be solved urgently in the future data intelligence track is how to express the most valuable activities of customers with data and precipitate data assets." Zhao Jiehui, chairman and CEO of Dipu Technology, said in an interview.
But data empowerment is easier said than done.
On the one hand, from the demand side, with the development of the Internet, C-end users continue to pursue a smoother and faster user experience, and for the sake of a rapidly changing market, flexible and agile decision-making is also crucial for enterprises. Therefore, the demand for real-time data processing in both 2C and 2B scenarios is increasing, and the explosion of data volume and the variety of data types have greatly improved the difficulty of real-time processing.
On the other hand, if we think about the practice of data intelligence from a higher dimension, it is not difficult to find that forming a closed loop of data circulation and application and building a data governance system is the "pain point" of most enterprises.
Although the upgrade of terminal technology and the cloud of enterprise systems have greatly reduced the cost of data collection and storage, because data is scattered in different business systems, each business system is often "self-contained", and the data interface and data storage methods are different, which leads to easy collection and difficult application of enterprise data, not only can not form a unified data caliber and definition, lack of unified management, and the cost of interpretation in the application process is high, which directly causes data decision-making to fail.
At the same time, the application of data by enterprises often follows the process of "collection-storage-analysis-application", and lacks a feedback mechanism for the effect of data application, so the data model is difficult to optimize and iterate in the application process automatically and intelligently, and the data experience is difficult to precipitate, which greatly reduces the "ceiling" of data potential.
In the face of many difficulties in the practice of data intelligence, the "14th Five-Year Plan" Big Data Industry Development Plan (hereinafter referred to as the "Planning") issued by the Ministry of Industry and Information Technology in early December 2021 proposed to accelerate the aggregation of data "large volumes", strengthen the "diversity" processing of data, promote the flow of data "timeliness", strengthen the "high-quality" governance of data and promote the transformation of data "high value" enterprise practice methodology, and proposed to big data service providers to accelerate the development of specialization, engineering and platform. Cultivate scenario-based big data solutions, promote the requirements of industry data assetization and productization, and point out the direction for the future development of data intelligence.
In response to the goals and directions proposed in the "Planning", Dipu Technology has seized the new development opportunities of data intelligence and has already taken the lead in layout.
Based on the technology engine, Dipu Technology builds a product system with data intelligence as the core
Through years of practical insight and solid technical capabilities to cultivate market sensitivity, Dip Technology is strategically oriented to the future, and has made simultaneous efforts at the technical, product and scenario levels to create a core product system matrix:
Technology Bottom Layer:
FastData, a cloud-native data intelligence platform, includes DLink, a stream-batch integrated data analysis and processing engine, DataFacts, a data intelligence development platform, DataSense, a data science analysis platform, and DXP, a data asset management and operation platform.
FastData adopts the storage and computing separation architecture, which can solve the storage and analysis problems caused by the large number, wide source and type of heterogeneous data, provide real-time second-level data processing and analysis capabilities, open up the data of various process nodes of the enterprise, reduce the cost of storage and computing, efficiently empower the business, and help enterprises establish a new generation of data storage and computing platform and data science analysis platform that integrates flow and batch and lake warehouse.
Data Intelligence Consulting:
In order to innovate the business value of enterprises, Dip Technology has built a data-centered business value innovation consulting DIC, from preliminary consultation to field research, through rich industry service experience, it is committed to helping enterprises establish a quantifiable, traceable and sustainable "scenario-indicator-tag-model-application" data asset system, helping enterprises to precipitate data assets from top to bottom, and supporting real-time intelligent decision-making for application scenarios.
Scene Empowerment:
Of course, the data application scenarios of different industries are quite different, so the main driving force and perspective of data asset management are very different, and there is no unified data governance solution for the whole industry.
For example, the manufacturing industry mainly focuses on the synergy of product data in the entire supply chain such as research and development, production, and sales, so it has higher requirements for data consistency and accuracy; the financial industry has higher requirements for data quality and security due to strict supervision.
Dip Technology combines the data circulation links and data governance requirements of different industries to create a solution with industry versatility. Up to now, Dipu Technology has been practicing in the fields of advanced manufacturing, biomedicine, energy travel, government affairs double carbon, financial technology, consumer circulation and other fields, serving more than 100 well-known large and medium-sized enterprises, and has achieved practical results.
Taking a large high-tech group as an example, a partner of Dipu Technology in the field of advanced manufacturing, as a large-scale high-tech enterprise group with military-civilian integration development, the group has completed the construction of the three core platforms of PLM, ERP and MES, but has not yet formed an integrated data link and data management.
Dip Technology helped the group build a unified data center of the group, running through the whole business chain from demand, design, manufacturing, supply chain, sales and after-sales, able to operate applications and precipitate industry data assets, improving the BOM accuracy rate from 92.3% to 96.6%, the core indicator automation rate from 62.2% to 76.9%, and the report automation rate from 40% to 90%.
But The data intelligence capabilities of Dipu Technology are not limited to this.
Facing the future of digital intelligence, the long-term strategy of Dipu Technology
Tapping the potential of data and promoting business innovation with intelligent technology is the trend of the times, and digital intelligence will also replace digitalization as the main driving force of the future digital economy. For the enterprise service market, technology tools may be rapidly iterative, user needs are constantly changing, and only forward-looking strategic decisions can help enterprises remain competitive.
"From the big policy background to the direction of enterprise development, enterprises have always been part of the trend of the times, so in the context of large policies, what enterprises need to do is to base themselves on reality, do their own things in a down-to-earth manner, and build long-term technical influence and core competitiveness." Zhao Jiehui said.
Comparing the development of the US market from SLG (Sales Led Growth, sales-driven growth) to PRG (Product Led Growth, product-driven growth), it can be clearly seen that PRG is based on "product power" as the core, willing to give up short-term growth, focus on long-term development model, so the development potential is greater.
Dipu Technology has captured the trend of china's enterprise service market to transform to the PPG model, thus becoming the forerunner of the PPG model - the establishment of bMT (Business Management Team), an organization composed of product units. Getting rid of the sales-oriented, disconnected product, supply-demand mismatched service model, BMT makes decisions from product development to delivery, so as to be able to better understand the margin of business capabilities and improve the fit with customer needs.
Under the general trend of China's enterprises moving to the cloud, building a data system in the cloud has also become the only way for enterprise business systems to go to the cloud. In order to meet the needs of cloudification, Dip Technology is focusing on the development of product cloud and capability expansion, and is committed to helping enterprises realize the potential of data value at low cost.
At the same time, in the face of more and more complex technologies in the field of data intelligence, Dipu Technology did not deliberately catch up with the technology trend, but took user needs as the core and selectively established technical competitiveness.
"Insist on selectively doing what you are good at and establish independent thinking ability" is the principle that Dip Technology has always adhered to for 3 years. In view of the core technologies such as the integration of lake warehouse and the integration of flow and batch computing, Dipu Technology has created a group of professional technical team personnel and data scientist teams, and has 192 software copyrights and 52 core patents declared so far, which has a leading edge in key technologies.
Whether it is for individuals or enterprises, long-termism is a challenge against human nature, not only testing professional level and operational ability, but also testing the strategic patience and mental strength of a leader and an organization. Nowadays, Dipu Technology has gradually established the core capabilities and technical barriers of data intelligence in just 3 years, which is the strategic vision of Dipu Technology to focus on the future and the long-term strategic spirit based on the present.