How Kuaishou’s Data Platform Powers Intelligent BI with AI and Big Data
This article outlines how Kuaishou’s Data Platform Department enhances decision‑making efficiency by building advanced compute engines and high‑performance services, detailing the platform’s architecture, challenges of intelligent BI, AI‑driven solutions, and the end‑to‑end BI workflow from data ingestion to analysis.
Background
Kuaishou Data Platform Department aims to improve data decision efficiency by building advanced compute engines and high‑performance data services, providing comprehensive data analysis support for business. It ranks among the top domestic data platforms, offering a self‑service BI toolchain from data ingestion to advanced applications.
Challenges and Solution Approach
With the rise of intelligent BI, the platform faces diverse user demands, data quality issues, and technical implementation challenges. Kuaishou proposes a controllable process, trustworthy results, and feasible models, leveraging AI to continuously optimize intelligent analysis and achieve large‑scale, low‑cost deployment.
Platform Architecture
The platform consists of three layers:
Business Layer : DA products for individual users, operational platform products, and B‑side services.
Product Layer : General BI product (KwaiBI) and specialized analysis products for domains such as the main site and e‑commerce.
Service Layer : Gaia standard metric middle platform and API platform, providing data set query, KV point‑query, and SQL table query services.
BI Overview
Business Intelligence (BI) transforms complex data into actionable information for decision‑making. A typical BI workflow includes data ingestion, relational modeling, and data application for analysis.
Data ingestion: Connectors import various data sources into the BI platform.
Relational modeling: Define user‑friendly metrics and dimensions.
Data application: Perform analytical calculations such as regional GDP distribution.
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