Financial Enterprise Big Data Platform Construction Plan: Architecture, Design, and Implementation

The plan uses a financial company's data‑warehouse project as a case study, analyzing the rapid growth of structured and unstructured data, data‑island problems, and the need for a high‑performance, scalable, and cost‑effective solution.

It proposes building a commercial‑edition Hadoop‑based data‑warehouse to fully exploit data assets, integrate source systems, and provide high‑quality business data views for analytics and decision‑making.

The architecture is divided into five layers: data source, storage & management (Hadoop + FS‑LDM), data application, data presentation, and final‑user layers, each with specific design principles such as neutrality, extensibility, stability, and usability.

Transwarp Data Hub (TDH) is recommended as the core platform, offering full SQL‑2003 support, PL/SQL, ACID transactions, high‑speed memory/SSD computation, and a rich library of distributed machine‑learning algorithms suitable for financial risk control and marketing.

Model design follows six steps—pre‑preparation, discussion, information research, unified business definition, customized FS‑LDM, and model verification—ensuring consistent naming, data‑type definitions, layout, and documentation standards.

Implementation is organized into four phases with detailed tasks, hardware/software configuration tables, and a project‑management timeline covering eight stages and 40 work items.

The final goal is to establish an enterprise‑wide big‑data platform that aggregates, processes, and analyzes structured, semi‑structured, and unstructured data to support decision‑making, product innovation, cross‑marketing, process optimization, and risk control, achieving shared and sustainable data value.