In the realm of data analysis and decision-making, businesses encounter various challenges such as inconsistent data standards, a shortage of talent, high barriers to data usage, prolonged analysis cycles, and insufficient data-driven decision support. AI assistants help extract valuable insights from big data, significantly enhancing corporate decision-making. By analyzing historical data and market trends, these tools provide a scientific basis for strategic planning and generate customized recommendations that improve decision-making processes.
Shushi Technology has recently unveiled its latest intelligent analysis product, SwiftAgent 2.0, which revolutionizes how businesses handle data analysis and decision-making. This product features key enhancements:
1. Task-Oriented to Goal-Oriented: Shifting focus from completing tasks to achieving specific business goals.
2. From Data Uploads to Self-Service: Enabling users to independently access and utilize data.
3. Real-Time Analysis: Offering immediate insights instead of relying on delayed reporting.
4. Smart Decision Making: Elevating data-driven decision-making beyond traditional analytics.
5. Data Accessibility for All: Ensuring everyone in the organization can effectively use data.
SwiftAgent 2.0 integrates advanced data analysis capabilities with Shushi’s metrics and tagging products, catering to managers, data analysts, and business personnel. Its essential features include:
1. Unified Data Semantics: Establishing a cohesive semantic layer for metrics and labels, SwiftAgent 2.0 converts natural language queries into actionable insights and SQL queries. This feature simplifies the understanding of complex business semantics while standardizing data across departments for accurate, data-driven decisions.
2. User Intervention: The system guides users through their queries with options that refine their questions. For example, a request for recent sales data could lead to prompts like "Sales in the last 7 days," allowing for more targeted inquiries. User feedback, through "likes" and "dislikes," also helps enhance the system’s learning.
3. Continued Reflection Learning: Utilizing reinforcement learning, SwiftAgent 2.0 builds a knowledge repository from past user interactions, improving its responses to similar queries over time.
4. Diverse Data Connection: The platform supports integration of various data sources, including data warehouses and unstructured formats like text, Excel, and audio/video content. This broad connectivity allows for comprehensive analysis, such as examining economic indicators and their impacts on market trends.
5. Hyper Computing Acceleration: Powered by a proprietary data computing engine, SwiftAgent 2.0 processes data queries at lightning speed, facilitating real-time human-computer interaction. With robust engines like StarRocks and Doris, it excels in managing complex queries while offering pre-calculation and data virtualization capabilities to enhance data utilization.
In summary, SwiftAgent empowers managers and frontline staff to access and leverage data effectively, transforming everyone into a data analyst. This democratization of data significantly lowers the barriers to analysis and emphasizes the vital role data plays in business decision-making, maximizing its value for organizations.
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