Exploring Indicator Platform Construction: Architecture, Methods, and Future Directions by Shusheng Technology

Driven by the growing demand for digital business capabilities, Shusheng Technology shares its experience in building an enterprise‑wide indicator platform that unifies strategic goals, improves data governance, and accelerates metric production.

Industry Exploration : The article identifies two core problems—slow development cycles and chaotic metric definitions—caused by limited data‑team resources and lack of centralized standards.

Solution Modes : Three approaches are discussed: (1) Agile BI at the application layer, enabling self‑service analytics but still suffering from metric inconsistency; (2) Data‑warehouse‑level solutions that improve governance yet remain slow for business requests; (3) Headless BI, a decoupled layer that standardizes metric definitions and supports cross‑application reuse, exemplified by Airbnb’s Minerva platform.

Smart Indicator Platform Design : Shusheng proposes three production models—light, heavy, and integrated “production + consumption”—each addressing different data‑warehouse maturity levels and emphasizing flexibility, reusability, and automated governance.

Product Architecture (SwiftMetrics) : The platform consists of four layers: data ingestion (StarRocks), data preprocessing (metric production and performance‑acceleration engine), service layer (metadata and query APIs), and gateway/user‑management layer. SwiftMetrics optimizes query plans through cost‑benefit evaluation and strategy routing.

Key Capabilities : Metric production (semantic modeling), metric consumption (API‑based access), and query acceleration ensure low‑threshold, high‑performance self‑service data retrieval.

Application Case : A retail group adopted the platform, achieving 20 % of metric development by technology and 80 % by business users, reducing duplication, improving timeliness and accuracy of analysis, and enhancing overall digital capability.

Future Outlook : Planned enhancements include real‑time metric support, expanded industry templates, AI‑driven intelligent services, richer visualization, and continuous optimization of the SwiftMetrics engine.