Recently, the second session of the 2023 Enterprise Digital Growth Seminar with the theme of "Exploring New Growth of SaaS, AI + Analytics Empowering the New Value of SaaS" jointly hosted by Hengshi Technology, Amazon Web Services, and Frontline Digital Intelligence was successfully held in Shanghai. CEOs, CIOs and other executives from dozens of SaaS enterprise service companies gathered together to explore how new AI technologies can empower and create new value for SaaS, and how to reduce costs and increase efficiency through ecological cooperation.
Hengshi Technology is deeply engaged in the BI field, constantly innovating, and has become a representative manufacturer focusing on integration and embedding cooperation in the BI field. At the event, Liu Chengzhong, the founder of Hengshi Technology, brought the theme of "AI + BI based on the indicator middle platform, helping SaaS reduce costs and increase income", and shared the new trend of BI technology with the guests. Here's a recap of sharing:
**In the next 3-5 years, BI will be enhanced in four areas
One is SaaS. Based on the cloud-native BI architecture, it has higher flexibility and scalability than traditional BI, and the delivery process is more efficientWhen all basic data and business data are migrated to the cloud, data analysis takes place when the data is in the cloud, and users can access and analyze in the cloud anytime and anywhere, lowering the threshold for analysis.
Second, BI analysis is more scenario-based, and is combined with vertical business application scenarios in practical applications. Analytics and reporting capabilities should be at your fingertips on the business side for real-time and direct business intelligence enhancement.
Third, the ability to manage indicators is more important. As BI spreads to the operational side, this will become more and more perceived, and the solution that represents the business know-how is actually the process of refining the business indicator system.
Fourth, AI-enhanced assistants will become mainstream. The emergence of AI has changed the entire BI usage form, users can complete the analysis by asking questions, lower the threshold for BI use, promote data analysis from the scope of data analysts to the whole company, so that everyone can easily access the service, and realize the popularization of analysis.
Migrating data to the cloud makes SaaS BI possible
Recently, Yunqi Technology and Hengshi Technology jointly released an integrated analysis solution on the cloud, which completes the construction of the cloud data foundation to a simple and effective BI-end application through the integration of the whole process of data, bringing users a full real-time intelligent analysis experience.
At the data warehouse level, Clouder proposes a single-engine technical concept, adopts three computing forms: unified batch processing, real-time stream data processing and interactive processing, and unifies data storage and management through the lakehouse platform to achieve simple and integrated platform services, which greatly simplifies the process of enterprise data construction and breaks through the shackles of offline data or real-time lambda architecture.
At the analysis level, through the semantic layer more suitable for data analysis developed by Hengshi BI PaaS, the end-to-end data analysis architecture innovation has been completed, and the open architecture of the lakehouse and the analysis pipeline architecture of ELT + EMBED have been developed, which will put the calculation behind and reduce the repeated processing of data. In addition, Hengshi supports multi-tenant adaptation, API service capabilities and elastic expansion on the cloud-native architecture, providing a lower cost and more flexible option for SaaS enterprises to build BI capabilities.
This cloud-based integrated solution cooperated by Hengshi and Yunji mainly provides services for SaaS enterprise partners. For SaaS companies, it is very attractive to reduce the cost and ease of use to a reasonable range, and reduce the cost of data computing and storage, as well as the cost of manual operation and maintenance, to less than 30%. The actual cost of building a data warehouse in the cloud and computing various data applications with different engines is very high, and this solution can reduce the cost to a fraction.
This cooperation is the first time that Hengshi has made efforts on the cloud, and the cooperation between Hengshi and Yunji will greatly reduce the cost of cloud analysis, and SaaS BI is no longer a castle in the air.
Embedded BI for industry software vendors
Overseas customers attach great importance to the purchase of tool software, and domestic customers are not Xi to do their own analysis, they prefer to directly obtain analysis reports in CRM, ERP and other business scenarios, so business software service providers generally need to provide BI capabilities in business scenarios to enhance services in recent years, BI capabilities will be embedded into various business scenarios in the form of engines, rather than landing in the form of professional tools, which is domestic BI The market is an interesting place in terms of Xi usage.
For industry manufacturers, the integration of Hengshi's BI can improve the efficiency of product development. After integrating Hengshi, a financial partner can develop an index middle platform solution based on Hengshi's BI and indicator management capabilitiesAnother marketing industry partner used the precipitated industry know-how to polish a standardized product of marketing insights based on the business analysis scenarios made by Hengshi.
Hengshi's product architecture has a high degree of openness and scalability, which can split data preparation, aggregation, modeling, analysis, visualization and other capabilities into standard functional modules, and provide APIs for all functions, which can be flexibly embedded in partners' own business systems to help partners reduce R&D costs. At the same time, for end customers, because it is integrated and embedded in the business scenario, there is almost no implementation process, and customers only need to analyze business data by dragging and dropping, which greatly improves the flexibility and responsiveness of analysis.
At present, hundreds of software and SaaS vendors have embedded and integrated Hengshi BI PaaS and become an in-depth partner of Hengshi. These partners cover various vertical fields, such as CRM, HR, financial and tax control, marketing, etc., and cover more than 100,000 end enterprise customers through this partner ecosystem.
Self-service metrics-based analytics
Domestic BI is still in the early market stage, and many customers are not yet able to use it. In the traditional BI architecture, data needs to be entered into the data warehouse for data processing, and then reports are created and published through BI. When the needs of the business department change, the KPI indicators that need to be redefined by data engineers need to be translated into data language, and the data needs to be reprocessed and modeled, and the data and analysis are separated in this process, resulting in the results being obtained after each new analysis requirement put forward by the business department, and the progress is seriously lagging behind, resulting in a high threshold for data analysis, which is difficult for the business side to really use and popularize within the enterprise.
Different from the traditional BI, Hengshi puts the data conversion and calculation process behind at the architecture level, and decouples the data from the analysis through the self-developed logical semantic layer (HQL), so that users can take the indicator as the center and define relevant business indicators through HQL semantics for data analysis, so as to eliminate the inconsistency of data caliber, reduce the repetitive processing and modeling process, greatly reduce the workload of data processing, and business personnel can also truly conduct self-service analysis. At the same time, Hengshi's indicator definition and management capabilities enable users to establish a complete indicator management system on the platform, realizing the transformation from traditional BI to self-service agile BI and then to business autonomous indicator BI.
From BI PaaS to AI PaaS
With the breakthrough of AI technology, everyone is looking forward to what kind of changes AI will bring to BI, in fact, the two still have completely different connotations and definitionsThe application scenario of BI is actually the best landing scenario for this advanced technology.
Some industry partners have tried to introduce AI, but the feedback has not been satisfactory, and the questions asked by users are not answered accurately, and the answers given by the AI are divergent. In terms of implementing AI technology in the BI field, the best model in the industry is Copilot. There are three main reasons why ChatBI's extensive attempts have failed: first, data control;The second is correctness verification, which makes it difficult for users to verify the correctness of AI answersThe third is domain modeling, the industry insight of most professional vendors is higher than that of large models, and the risk of data security makes it difficult to improve the capabilities of large models to the industry level through model training. In contrast, small models in vertical industries will be more reliable.
AI augmentation in BI is not just a conversation, but a real-time question. When the user is analyzing, they get a real-time response by asking questions. In addition, users can ask questions to get refined feedback based on the content of the report. Hengshi's research on AI enhancement capabilities focuses on whether it can be repeatedly questioned and excavated deeply.
The core advantage of the AI-enhanced analytics capabilities provided by Hengshi is chat2metrics. In terms of functional design, Hengshi Sense uses the powerful natural language understanding of large models and is based on the platform's indicator system, allowing users to ask questions about the system and realize various business reports and analysis functions. Hengshi's self-developed HQL semantics make it easier to express complex business indicators and control permissions than SQL. In terms of use, the platform adopts the form of AI Copilot, which evokes an intelligent assistant on the dashboard, and users can ask further questions about it. In addition, the platform provides a general large model invocation framework, and users can choose the appropriate large model according to their own situation.
About Hengshi Technology
Hengshi Technology defines a new generation of AI-powered analytics intelligence platform, focusing on enabling enterprise customers and SaaS ISV vendors across the industry to build analytics applications agilely. Its core product, Hengshi Sense, allows partners to easily launch functions such as AI Copilot, BI analysis, indicator middle-end, and operation dashboard in their own business scenarios to drive the intelligent transformation of their business. Hengshi Technology has been with Amazon Web Services, Baozun E-commerce, Haofang Group, Jijia ERP, Lingxing ERP, Tanma SCRM, Micro Companion Assistant, Fanxiang Sales, Liudu Renhe, Weiling Technology, Siwei Technology and other hundreds of advanced SaaS ISV manufacturers have landed in-depth cooperation, so that scenario-based business analysis is immediately online, ecological cooperation has covered digital marketing, ERP, CRM, SCRM, CEM, HR, industry and financial cost control, MES, low**, chain management and other vertical fields.
powered byhengshi