2022 China’s Data Middle Platform ReportSource:iResearch
November 15,20223:07 PMOverview
The size of the data middle platform market reached 9.69 billion yuan in 2021. On the supply side, the industrial ecological cooperation trend is obvious. On the demand side, data monetization ability, rather than the data middle platform, attract the most attention. The industry is more and more concentrated and mature. Its size is growing steadily and is expected to reach 18.74 billion yuan in 2024.
The industry concentration is still low. Platform ecological vendors, solution providers and independent middle platform vendors are the main active participants in the industry. The industry environment will change from competition to co-opetition. Taking collaborative ecology as the core, they gather their strengths, combine mature technical solutions with industry service experience, and synergistically expand the breadth and depth of application solutions, focusing on financial, pan-retail, government affairs, manufacturing and other industry application scenarios.
Cloud-native is now the most certain technology trend. Core technology elements such as separation of storage and computing, microservices and ServerLess drive data middle platform toward cloud native. The concept of data and intelligence integration uses AI algorithm models for data governance, and high -quality data for improving development capabilities, realizing efficient communication between data and AI development. The trend of the pan-middle platform is increasingly prominent. The solutions and products demanded in business scenarios are increasingly like middle platforms. The middle platform system based on data middle platforms becomes increasingly rich.
Data middle platforms are committed to dealing with the original data relationship and SOA architecture, solving the ‘data chimney’ problem, connecting data silos, and enhancing data governance and data availability. Realize data capitalization through improving data standard systems, strengthening data quality control, unified management metadata, and other methods. When transforming enterprises' business processes, data middle platforms remove not only the data barriers but also the business barriers between different departments and business groups in a company, largely improving organization flexibility. Data middle platforms are designed for enterprises' top-level strategy, reflecting the top-level framework and business logic. The development and application of all enterprise data assets by data middle platforms bring data the agile service capability. All levels of the enterprise can intelligently and quickly invoke data service capabilities to maximize the value of data and empower b business decisions.
In China, the digital economy is booming, enterprises‘ digital transformation is accelerating, and data technology facilitates innovative integration and application. The data middle platform industry was born in 2019. It quickly passed the budding and growth stages and is entering the mature stage. From the perspective of supply, the ecological cooperation trend is prominent. Cloud vendors are accelerating the cooperation deployment in various vertical fields. Thanks to their ecological partners’ industry experience accumulation and service collaboration, their personalized deployment capabilities and implementation efficiency have been significantly improved. At the same time, some independent vendors integrate the underlying platform capabilities of cloud vendors with their own technological innovations and advantages to create diversified data middle platform products. As to demand, enterprises have shifted their attention from data middle platforms to their data monetization capability. As enterprises’ understanding of middle platforms deepens, their demand becomes increasingly clear. In addition, influenced by the pandemic, they are more price sensitive. In addition, since enterprises influenced by the pandemic have become more price-sensitive, vendors have to actively explore new business models and upgrade their services. The data middle platform industry is increasingly concentrated and mature. Its overall scale grows steadily, and the growth rate is stabilizing.
In recent years, the application of data middle platforms has been fast in many scenarios thanks to the development of technologies such as big data, cloud-native, artificial intelligence, and accelerated digital transformation of enterprises. In terms of the types of vendors, the boundaries between platform ecology vendors, solution providers, independent middle platform vendors, and independent R&D vendors begin to blur. The ecological synergy of data and intelligent services is obvious. From the perspective of the market landscape, cloud service providers rely on their complete service system and strong ecological capabilities to output methodology, technology and tools, establishing an industry service system; With innovative technology capabilities and a deep understanding of businesses in vertical industries, product producers achieved to enhance their brand competitiveness.
Coopetition, instead of competition, is becoming the relationship between vendors. They take the collaborative ecology as the core, gather strengths, and work together to expand the breadth and depth of collaborative application solutions. Platform ecology vendors have a first-mover advantage. They are the first to implement the middle platform strategy and provide services, contributing methodology, technology, and tool systems to the development of the industry. They mainly provide cloud infrastructure services, while their ecosystem partners implement and deliver. The solution providers have accumulated rich vertical industry service experience and a customer service foundation. They can quickly and precisely gain insights into an enterprise's business processes, pain points and demand. However, their project implementation delivery usually needs external data capability support. The core technical teams of independent middle platform vendors are mostly from industry leaders. They have great technical capabilities, and rich industry experience but their brand influence is weaker than platform ecology vendors.
Thanks to technology development, the implementation of a middle platform has become less difficult. However, middle platform construction is not the right choice for all companies. The middle platform’s data convergence and connection feature requires enterprises to have accumulated and applied or will soon accumulate and apply a large amount of data. If a company is not large, or if it is large but has few business lines, it would be more cost-effective to deal with data demand one-on-one. The feature of reuse only suits enterprises with businesses that will change and business lines that are connected. It wouldn't be necessary to build a middle platform if an enterprise has very stable businesses. To use a middle platform, an enterprise needs a supporting mechanism involving corporate strategy, organizational structure, etc. If a company has no dedicated data department and only relies on business departments, it will be difficult since all business departments want to use data but none of them is willing to contribute, build or govern data. In short, the middle platform serves as infrastructure. Its steady base ensures the agility of the upper layers, its public construction guarantees the use by different business lines, and the current heavy investment will yield high output in the future. Middle platform is not totally Any company with different planning should use a module of the middle platform instead, such as data warehouse, data lake or main data governance to solve their current problems first.
Since the financial industry started informatization construction early and has invested heavily in it, its informatization level and data standardization level are high. It has a relatively complete digital service ecology. However, due to the traditional digital solutions, most financial institutions have multiple information departments and data centers. With the diversified development of business and accumulation of massive business data, a lot of systems, functions and applications are being built repeatedly. There is a huge waste of data resources, computing resources and human resources, and the problem of information islands is serious. It is difficult to plan internal and external data in a well-coordinated way. Their data capabilities cannot cope with high concurrency, strong consistency, and horizontal expansion of business scenarios. Financial institutions with leading data transformation have started building data middle platforms. Data middle platforms collect and integrate data from multiple databases in financial institutions to establish a leaping data model and break data barriers. They process data, and output standard data in a unified manner, establish data assets, reduce duplication of business data construction, and change data delivery models in the financial industry, forming professional user portraits to support precise marketing and operation decision-making, and improve customer operation efficiency.
Trend: Cloud Native
Cloud native is the most certain technology trend, and it is jointly driven by mainstream technologies such as Docker + Kubernetes and Spring Cloud. However, nowadays, a lot of the so-called ‘cloud native' is only a transformation of the traditional monolithic architecture. It can not actually achieve full elastic scaling of resources. The separation of storage and compute and their dynamic expansion and contraction can help balance cost and efficiency. This guarantees the low-cost application of big data, and will also be a distinctive feature of cloud native. In the future, the data storage of middle platforms will surge. High throughput and high concurrency put forward higher requirements for the separation of storage and computing. Important components of data middle platforms, such as MPP and Smart Lake Warehouse, will be in line with the storage-computation separation architecture. In addition, enterprise clients will pay more and more attention to data security. They will have rising demand for data security, compliance data cooperation technology, etc. Cloud native's natural technical attributes, such as object architecture, containerized orchestration, CI/CD (continuous integration and continuous delivery), and cross-cloud and multi-domain data governance, will drive data middle platforms to develop toward cloud native.
Table of Contents
1 Overview of Data Middle Platform
1.2 Driving Factor: Macro Level
1.3 Driving Factor: Industry Level
1.4 Driving Factor: Enterprise Level
2 Overview of the Data Middle Platform Industry
2.1 Size of the Data Middle Platform Market
2.2 Industry Map
2.3 Industry Landscape
2.4 Industry Challenges
3 Industry Application of Data Middle Platforms
3.1 Demand Analysis
3.2 Overall Analysis
3.3 Core Methodology
3.4 Manufacturer Vendor
3.5 Data Management Mechanism
3.6 Base Technology Selection
3.7 Data Governance
3.8 Data Asset Management
3.9 Data Service
3.10 Data Guarantee
3.11 Industry Scenarios
3.11.1 Financial Industry
3.11.2 Pan-retail Industry
3.11.3 Government Affair Industry
4 Case Study
4.3 MININGLAMP TECHNOLOGY
4.4 NetEase Digital Sail
4.5 VP HONOR
5 Industry Outlook
5.1 Cloud Native
5.2 Data and Intelligence Integration
5.3 Internet of Everything
In a narrow sense, the data middle platform is a tool to realize data asset and service reuse; In a broad sense, it is a mechanism and a methodology for promoting enterprises' digital transformation and upgrading by data. Starting from the accumulation of business data, data middle platforms are used for data collection, integration, analysis, and application, forming an ecological closed loop.
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