This guide presents a systematic approach to improve data warehouse modeling by enhancing model completeness, increasing reuse through unified dimensions and services, and enforcing naming and governance standards, supported by quantitative goals, practical strategies, and real‑world case studies.
This article explains how ClickHouse’s columnar storage, bitmap functions, and distributed architecture can be leveraged to store billions of tag bitmaps, combine them efficiently, and support fast group calculations for customer data platforms, while addressing data‑warehouse integration, storage format, and performance challenges.
This article provides an in-depth overview of metadata concepts, their technical and business classifications, value in data management, applications such as data profiling and lineage, optimization techniques for compute and storage, lifecycle management, and comprehensive data quality assurance practices within large‑scale big data environments.
This article details how Alibaba's TCC platform evolved its architecture over multiple phases—from a legacy database to a high‑availability real‑time data warehouse built on Flink and Hologres—highlighting the challenges, solutions, and cost‑saving measures that enabled millions of RPS, terabytes of storage, and sub‑second query latency.
Alibaba Cloud’s Hologres unifies analytical and service workloads in a real‑time data warehouse, simplifying data exchange, reducing development and operational costs, and delivering high‑performance, low‑latency online services through innovations like row‑column hybrid storage, hot upgrades, and elastic cloud‑native scaling, as demonstrated in a logistics case study.
MaFengWo’s data platform replaced Kylin, Presto, and Druid with StarRocks, redesigning its four‑layer architecture, unifying metadata, and optimizing single‑table, multi‑table, and precise‑deduplication queries, which cut query latency by four times, reduced storage by 87%, and lowered operational complexity.
This article explains the growing demand for real‑time data warehouses, outlines their objectives and layered architecture, and presents detailed case studies from Didi, Kuaishou, Tencent, Youzan and others, illustrating design choices, implementation challenges, and best practices for building scalable streaming data platforms.
