Table of contents
1. Definition of research scope
2. Market Analysis of Business Intelligence Application Solutions
3. Vendor evaluation: Shuju shares
4. Certificate of Selection
1. Definition of research scope
Business intelligence (BI) is based on the realization of data integration and unified management, using technologies such as data storage and processing, analysis and display, to meet the needs of different groups of people in the enterprise for data query, analysis and exploration, so as to transform data into meaningful Information and knowledge of commercial value, thus providing data basis and decision support for enterprise management and business operation.
The "14th Five-Year" Digital Economy Development Plan issued by the State Council in 2021 points out that data elements are the core engine for the development of the digital economy. With the generation and accumulation of a large amount of data in the construction of information technology, many people realize the importance of data to the competitive advantage of enterprises. The massive accumulation of data contains huge value and brings new opportunities for the development of enterprises. From the perspective of enterprise digital transformation, business intelligence's superior data value mining and data analysis and decision-making capabilities can help enterprises establish a data-driven decision-making management method and realize the reshaping of business, process and management methods by enterprise digital transformation.
From the demand side, enterprises' demand for business intelligence is not limited to simple query analysis and result visualization, but also needs to establish a complete data application system to fully release the value of data. The first is to break down data islands, build a unified data integration management and application system, conduct real-time and agile analysis, and improve the efficiency of data acquisition and use to cope with the changing speed of the market environment and increased uncertainty; second, It is to enable everyone to have the ability of data analysis, transforming from traditional extensive experience-driven to rational data-driven, so as to improve the accuracy of decision-making and form a digital operation coordinated by the whole enterprise.
From the perspective of the supply side, business intelligence also provides services in a form that is closer to business scenarios and user needs in the context of continuous development of data technology and continuous improvement of enterprise demand, combined with emerging technologies such as artificial intelligence and cloud computing. In terms of solution composition, manufacturers began to sort out and summarize data indicators around enterprise business scenarios, using indicators as the common language of enterprise management and the smallest unit that carries data value, and building an indicator center as a platform for enterprise digital management. In terms of technology, business intelligence combined with artificial intelligence technology has been expanded into an enhanced analysis tool, and its capability enhancement is reflected in two aspects: the first is to provide query analysis with a lower threshold based on natural language interaction, and the second is to enhance data insight through machine learning Ability to generate and interpret. In terms of usage, business intelligence is closer to users and provides services embedded in business scenarios to help users complete data query and analysis more efficiently.
From this, we can see that the concept of business intelligence has become more and more extensive, and more content has been gradually absorbed and expanded in terms of product solutions, technology integration, and usage methods. From initial technical tools to complete solutions, the business intelligence system is growing. Therefore, Aianalysis selects the key market research of business intelligence, provides market guidance information for Party A enterprises, and helps Party A enterprises understand the value of business intelligence.
Ai Analysis believes that from the perspective of technical architecture, the business intelligence market can be divided into platform layer, tool layer and application layer. The platform layer includes a one-stop data analysis platform and an indicator platform; the tool layer includes self-service analysis tools, embedded analysis tools, enhanced analysis tools, and data visualization; Business intelligence application solutions built in scenarios such as control, intelligent marketing, and performance management.
This evaluation report focuses on the business intelligence application solution market. Aianalysis selects manufacturers with mature solutions and implementation capabilities to provide reference for enterprises when selecting business intelligence application solution vendors. At the same time, in this market, Aianalytics focused on selecting the business intelligence application solution manufacturer Shuju Technology Co., Ltd. for capability assessment.
2. Business Intelligence Application Solutions Market Analysis
Market Definition:
Business intelligence application solutions are business intelligence systems, applications and related project services provided to solve specific business scenarios or management needs of enterprises, and integrate data connection, data processing, data analysis and display capabilities and scenario-based business intelligence applications , and provide a series of service support from project planning, project system development and implementation to system operation and maintenance management.
Party A’s end users:
Business personnel, IT personnel, front-line managers, and corporate decision-makers in various departments of the enterprise
Party A's core needs:
In the process of digital transformation, enterprises have realized that business intelligence is an important way to release the value of data, and have used some related products more or less. However, in the face of professional and general-purpose tools, some companies encounter the problem of "not using" or "not using well" due to lack of mature analysis methods or practical experience, so it is difficult to discover effective information to improve business pain points Or strengthen enterprise management, resulting in a situation where digital transformation is out of touch with actual operation management needs.
Figure 1: Party A’s core needs
Therefore, enterprises hope to incorporate operation management methodology or data analysis practical experience into the tools, and assist decision-making or optimize business in a way that is closer to their own thinking or usage habits. Specifically, businesses want to:
- Build a unified and complete application platform around the core requirements of analysis and visualization. Faced with large-scale and scattered data resources, enterprises hope to build a unified platform environment for data source access, data integration and processing, analysis and display. At the same time, the application platform should support the development of various scenario-based applications.
- Obtain data applications that are closer to management or business scenarios. In terms of internal management, enterprises hope to grasp various data and information such as business dynamics, financial status, and potential risks in real time, and use this as a basis to make timely decisions and implement actions. In terms of business operations, enterprises hope to locate and improve business problems in a timely manner through data, or independently find breakthroughs to reduce costs and increase efficiency, and form standardized and reusable data application templates. Due to the diversification of internal requirements and high development costs, enterprises need a single or multiple combined business management theme modules to form productized data applications.
- Reduce the use threshold and learning costs, and meet the needs of different roles to apply data-driven decision-making and optimize processes. For business personnel, a large number of manual reports, manual statistics and other operations involved in business operations need to be replaced by more agile and flexible business analysis methods, so as to improve work efficiency and accuracy; for IT personnel, reduce the time and labor costs of developing reports , Improving the efficiency of enterprise digital construction is the main appeal; for front-line managers or enterprise decision-makers, they hope to understand business operations or enterprise operations in real time, locate and analyze problems in a timely manner, and use data to support decision-making.
- Possess stable and reliable big data real-time analysis capabilities. With the awakening of digital management awareness, everyone in large organizations will use data analysis functions, but the data volume and personnel scale of enterprises will inevitably put pressure on the efficiency of analysis work, resulting in slow or even impossible acquisition of analysis results situation. Therefore, enterprises hope to have a stable operating system to meet the needs of real-time analysis under large amounts of data.
- In terms of implementation and deployment, enterprises rely on certain technical support and practical experience references to ensure the success of the project. The large-scale system project of an enterprise includes a series of activities such as planning, development, and operation and maintenance management. Once the effect of the plan is not as expected, or there are problems in development or use, the enterprise needs to invest in cost for later transformation or maintenance. This work and Its difficult and burdensome. Therefore, enterprises need technical support in development and operation and maintenance management, and learn from successful experience to ensure the smooth operation of the project.
In addition, many enterprises have already deployed and used some analysis tools. In this case, enterprises expect:
- Continuously iteratively innovate tool application scenarios. First of all, enterprises are familiar with the data analysis products they are using, so they hope to continue to use them and explore new usage methods and scenarios based on them. On the other hand, enterprises hope to match the ever-increasing business or management needs by introducing new tools or solutions.
Manufacturer capability requirements:
In response to the above requirements, manufacturers must be able to provide mature business intelligence system products to meet the integrity, ease of use, high performance and stability of functions (basic functions and upper-layer applications), and have business intelligence application solution service experience. Specifically, vendors need to:
Figure 2: Schematic diagram of business intelligence system capabilities
- Provides the foundational functionality of a business intelligence system within one solution. The basic functions of business intelligence include data collection, data integration and processing, data analysis and visualization, etc. The data collection stage must be able to connect multiple data sources inside and outside the enterprise; data integration and processing must support operations such as data extraction, cleaning, and conversion, and efficiently and conveniently build a data warehouse; data analysis and visualization must be flexible and agile, so as to satisfy users. Dimensions, requirements for roll-up and drill-down exploration of different data indicators. At the same time, the system must have the ability to convert scene requirements to facilitate the construction of upper-level business intelligence applications.
- Possess certain industry know-how and business intelligence project experience, and be able to build commercialized business intelligence applications according to scenario requirements. For typical business intelligence functions, manufacturers must be able to create data applications such as management cockpit, Chinese-style complex reports, and self-service analysis according to user needs. In view of the differences in business needs of different industries, manufacturers should consider how to better combine analysis and visualization tools with specific scenarios, such as supply chain management, smart marketing, smart risk control, etc., to effectively improve business efficiency and accuracy.
- Provide easy-to-use front-end applications that meet the needs of different roles. Because the functions of personnel who use business intelligence are different, and there are not small differences in IT usage capabilities, it is very important to face different end users, how the interactive experience is, and whether they can meet the needs. The manufacturer's solution should minimize the user's learning cost and use threshold on the basis of meeting the user's needs. In addition, the ease of use is also reflected in the richness of learning resources. Additional learning resources can help users further improve the ability to use tools after getting started quickly, and create more data application value.
- The high-performance business intelligence system provided ensures the speed and quality of operation. The performance of a business intelligence system determines the response speed of query analysis, especially in scenarios with large amounts of data and multi-dimensional complex calculations. The performance of the business intelligence system provided by the manufacturer must be able to meet the high concurrent real-time analysis requirements in large enterprises. At the same time, the business intelligence system provided by the manufacturer must be able to run smoothly in the enterprise IT environment to ensure that data services are not interrupted or stalled.
- Have a perfect service system to ensure the success of the project. Before project sales, manufacturers need to accurately understand user needs and expected benefits, and design feasible solutions; in project implementation, manufacturers need to provide technical support and customized development services; after project sales, manufacturers must have a complete problem-solving mechanism and The ability to respond quickly. All in all, the manufacturer's supporting services should help the project succeed to the greatest extent.
In addition, in the face of customers' needs to retain existing analysis tools, or to develop new applications:
- Manufacturers' solutions must have certain compatibility and openness. Good compatibility allows enterprises to continue to use existing analysis tools to form a one-stop data application system. The openness of the solution is reflected in the convenience of connecting various third-party analysis tools, software products or functional modules, speeding up product function upgrades and iteration efficiency, and ensuring project continuity.
Inclusion Criteria Description:
- Comply with the manufacturer's capability requirements in the market definition;
- From 2022Q1 to 2022Q4, the number of enterprise-level paying customers in this market is ≥ 10;
- From 2022Q1 to 2022Q4, the contract revenue of this market is ≥ 10 million yuan.
Manufacturer panoramic map:
3. Vendor Evaluation:Shuju shares
Manufacturer introduction:
Shanghai Shuju Software System Co., Ltd. ("Shuju" for short) was established in 2009. It is a "specialized, special and new" high-tech enterprise focusing on digital transformation and intelligent transformation in China. The company provides software products related to big data , technical consulting and implementation services, especially providing one-stop solutions in data-driven management and data-enabled business.
Product service introduction:
Shuju Dimple DIMP® is a set of business intelligence application solutions independently developed by Shuju, which integrates enterprise management ideas and data science, and can be used for digital operation management of landing enterprises. Because it also has the function of a data portal, it can also be used as the only authoritative entrance for enterprise management data. DIMP® is data-driven, with a micro-service architecture as the framework, combined with data-driven management and data-enabled business scenario application modules, and implemented in the form of standardized software modules. DIMP® can integrate all mainstream analysis tools, has a single sign-on portal function, and has digital functions specially designed for business management, such as digital nerves, business index tree, sand table simulation, plan preparation, management canvas, digital large screen, and smart insights .
In addition, around business intelligence solutions, Shuju shares also provide visual data integration processing platform (VDIP), Shuju Yishi (E-Viz), Shuju Yiwen (E-Que), Shuju Yidao (E- Bui), Data Gathering Governance Platform (DGP), Data Gathering Exchange Platform (DXP) and other instrumental products.
Shuju has served nearly a thousand customers in various industries such as manufacturing, distribution and retail, government, finance, modern services, etc., and has accumulated rich industry experience especially in the automotive sector, pharmaceutical sector, and hotel management sector.
Vendor Evaluation:
Shuju can provide business intelligence software with complete functions, easy to use, stable and reliable technology, good compatibility and scalability, and integrate best management practices to build application solutions. Shuju has accumulated rich experience in industry know-how and project practice. It can abstract the best practices of operation management or data application into product modules and integrate them into solutions, helping enterprises transform data assets into information and knowledge with commercial value. In terms of project planning and implementation, Shuju has a mature service system and is constantly iterating and innovating to ensure project continuity.
- Shuju shares efficiently combine one-stop data analysis with application scenarios, and builds a full-featured, end-to-end business intelligence application solution. The business intelligence application solutions provided by Shuju shares include Shuju Governance Platform, Shuju Easy to View, Easy to Ask and Easy to Build, and Digital Intelligent Management Platform, which can meet the whole scene of enterprises from bottom-level data governance, visual analysis to upper-level digital operation management and application need.
For specific scenarios such as business and financial integration, business analysis, and performance management, the intelligent management platform DIMP® also includes: indicator boards displaying business conditions and core indicators KPI, and pushing them to designated people through preset rules and time, scientifically realized Smart insight; decision-making plan preparation supports relevant responsible persons to draw up appropriate budgets and action plans through sand table deduction; there is also a special module to meet the needs of business management meetings and OKR management, through real-time and accurate data big screen Work report; in addition, the analysis results or decision-making plans can also implement actions through the action plan or comment function, and perform pre-actual comparisons on the execution results. Overall, DIMP® can help enterprises realize PDCA closed-loop management that transforms data analysis results into effective execution.
- Shuju has accumulated rich industry know-how in more than ten years of customer service, and can customize effective solutions according to the needs of different businesses or application scenarios. On the data governance side, it ensures the quality of the underlying data by providing modules such as data aggregation modeling and data aggregation governance. At the same time, it provides indicator system templates for different industry data characteristics to guide customers to improve the level of indicator application. On the data application side, in order to solve different business problems, Shuju Technology abstracts and summarizes the typical analysis logic and ideas in business scenarios, builds a data application model into the solution, and fully balances the end user's IT use ability and digital operation demands, forming a solution that is easy to use and has advanced functions.
In the past ten years, Shuju has served nearly a thousand customers, and has accumulated rich industry experience especially in the automotive and medical sectors. For example, the solution built by Shuju for a car dealer group integrates the idea of 4S store benchmarking management into the DIMP® system, and summarizes and compares hundreds of dynamically changing business indicators in different dimensions in real time. From group executives, operation management centers, 4S store leaders to front-line business personnel, they can independently obtain data through mobile terminals or PC terminals, and conduct in-depth analysis independently. At present, the platform has more than 2,000 users, covering 7 major business divisions and nearly 300 stores, with an average daily visit volume of more than 10,000, which greatly reduces the manpower, material resources and time costs of the company's implementation of benchmarking management.
- In terms of ease of use, DIMP® is oriented to actual usage scenarios, provides low-threshold self-service analysis tools, and uses intelligent insights to reduce the difficulty of decision-making management. For business personnel, DIMP® supports various forms of intelligent analysis such as correlation analysis, decomposition analysis, comparative analysis, etc., and can conduct flexible insights into business and financial conditions without the help of IT personnel. For managers, DIMP® integrates the best practices of enterprise digital management, and builds the judgment logic of business experts into algorithms or models, and monitors and alarms key indicators in real time in a way that is closer to the way managers think, so that managers can find business in a timely manner Abnormal operation and predictive decision-making have effectively improved the efficiency and accuracy of operation management.
- DIMP® technology is stable and reliable, and can be widely compatible and flexibly expanded. In terms of technical architecture, DIMP® is based on a standard modular micro-service architecture, which can provide high-performance, high-scalability, and high-fault-tolerance services for a large number of users in the enterprise. In terms of product compatibility, the standard API interface provided by DIMP® can seamlessly integrate various third-party software products, tools, and functional modules, helping organizations integrate mainstream analysis products and retain existing data assets. In addition, DIMP® can connect various databases, data sources and data warehouses, and break through the scattered data islands within the enterprise.
- Shuju has a complete service system and SLA standards to ensure the successful implementation of the project, and can continuously iterate products and solutions to provide long-term support for the digital transformation of enterprises. At the service level, Shuju shares provide one-stop services from digital management light consulting, project planning, business analysis, system development, project implementation, to training and after-sales service to help the project land, project configuration digital management light consulting team, delivery The implementation team and product after-sales service team are responsible for the smooth operation of the project and achieving the expected benefits of customers. In terms of the sustainability of the solution, Shuju actively pays attention to the trend of upstream and downstream technology changes and the surrounding ecology, maintains the ability to continuously upgrade and innovate product functions, and supports the digital transformation of enterprises for a long time.
Typical customers:
Yongda Automobile, Wanda Hotel Management Group, Fosun Pharmaceutical Group, Hengjie Sanitary Ware, KWG Pacific, Mizuho Bank, Changjiang Pension Insurance
4. Certificate of Enrollment
