Big Data Analytics Platform Series for Communications Administrations — DaaS Platform Solution Built on GBase UP Converged Architecture

DaaS Platform Built on the GBase UP Converged Architecture: This big data platform integrates stable, high-performance OLTP transaction databases, large-scale distributed parallel MPP database clusters for OLAP, and NoSQL technologies to handle massive volumes of structured, semi-structured, and unstructured data. It delivers a unified external interface with a scalable internal architecture, supporting data collection, storage, and computing across structured, unstructured, and semi-structured data. The platform adapts seamlessly to business scenarios requiring OLAP, OLTP, and NoSQL computing models.

Full Deployment Across Communications Regulatory Agencies: The GBase big data analytics platform has begun to replicate across the communications administration sector, forming comprehensive WA/XA project partnerships with system integrators.

This solution leverages the GBase UP Big Data Fusion Platform to build a standardized DaaS (Data as a Service) platform for unified data ingestion and access.

The platform comprises a Data Ingestion Layer, a Data Storage Layer, a Data Computing Layer, an Analytics Service Layer, and unified big data monitoring and management. The Data Ingestion Layer supports data collection, filtering, caching, relay, and dispatch scheduling.

The Data Storage Layer provides unified and reliable storage management for massive, heterogeneous data, offering standardized access interfaces for structured, semi-structured, and unstructured data.

The Data Computing Layer is built on a distributed computing framework that supports multiple computing models, providing professional computing libraries for upper-layer business systems.

The Analytics Service Layer provides various protocol and standard access interfaces for upper-layer business systems and enables cross-engine job scheduling within the big data platform.

The unified big data monitoring and management component handles operations, monitoring, and other functions for the data analytics platform, offering both command-line and graphical management interfaces.

The Provincial Communications Administration is the regulatory authority overseeing the telecommunications industry within its jurisdiction, exercising centralized supervision and management of the telecom sector. To support telecom network security analysis and industry regulation, the Administration's big data analytics platform is designed to provide integrated threat intelligence management and analysis. By centrally collecting massive heterogeneous data and performing security analytics, it identifies and surfaces potential threats.

The big data analytics platform must effectively support various business information processing and operations, delivering comprehensive capabilities for both online and offline data storage and processing while remaining easy to manage and scale. It needs to handle structured, semi-structured, and unstructured data, leveraging a scalable distributed architecture to efficiently enable data processing, retrieval, statistics, analysis, and in-depth mining. The platform should provide optimal resource and task scheduling, and ultimately offer upper-layer business systems data storage, retrieval, statistics, and analysis services through standard interfaces.