Enterprise-Level Data Warehouse Platform

1. Data Hierarchical Storage and Management Functions

1. Original Data Buffer Layer (ODM)

   Serves as a hub for source data access and buffering, supporting unified access to multiple types of data, standardizing data encoding and formats, cataloging by business systems, unifying naming conventions, and simplifying data update processes.
2. Historical Data Model Layer (HDM)

   Constructs partitioned and bucketed tables in ORC format, retains historical states of source data through two methods, implements full backup and incremental recording of data, and supports traceability and auditability with supporting log tables.
3. Common Data Model Layer (CDM)

   Cleans and integrates data based on the HDM layer, reduces redundant processing by deploying public data, stores data in snapshot and historical zones, and supports multi-dimensional summary analysis.
4. Master Data Management Layer (MDM)

   Acts as a unified export portal for external data services, provides interface tables and views, supports data supply inside and outside the cluster, unifies naming standards, and ensures consistency of downstream data.

2. Data Processing and Transformation Functions

1. Automated End-to-End ETL Processing

   Establishes unidirectional data flow, automates data extraction, transformation, and loading, supports differentiated processing of multiple data types, and stores data in standardized partitions.
2. Data Validation and Quality Control

   Performs validity checks on incoming data, triggers re-supply on validation failure, embeds quality statistics modules, records key indicators, and ensures controllable data quality.
3. Centralized Job Scheduling and Monitoring

   Builds a unified scheduling and monitoring platform based on supporting systems, supports job configuration by batches and dependencies, sends alerts on exceptions, logs events, and ensures stable 24/7 operation.

3. Data Service and Application Support Functions

1. Multi-Dimensional Data Service Interfaces

   Provides multiple access interfaces, compatible with mainstream BI tools, supports high-speed query and analysis of massive data, and enables various thematic analysis applications.
2. Data Analysis and Mining Support

   Integrates in-memory analytics engines and real-time databases, supports parallel computing and data mining, is compatible with multiple syntaxes, and meets interactive analysis and real-time query requirements.
3. Flexible Catalog and Permission Management

   Standardizes catalog structure, strictly controls directory permissions, establishes a three-level permission control system, and ensures secure data access.

4. System Management and O&M Functions

1. Environment Configuration and Deployment

   Supports deployment of three databases on a single TDH cluster with unified management, provides standardized catalog design specifications, and facilitates maintenance and expansion.
2. Data Archiving and Backup

   Automatically compresses and archives source data, stores data in standardized classifications, supports data rollback and recovery, and efficiently backs up core data in ORC format.
3. Monitoring and Log Management

   Records all logs based on the ELK stack, supports fast troubleshooting, monitors ETL job status in real time, and sends timely alerts on exceptions.