Enterprise-level Data Platform

Overall Planning

Data Service

Multi-level Dimensions

Operational Closed Loop

The data center focuses on breaking data silos & enterprise digital innovation, & maximizes the data value of the enterprise's existing data platform system by improving the integration service capabilities of data assets, reducing repeated application development $ sharing data value

Platform Introduction

"Data Center is based on the production of enterprise-level data assets to build a data service center"

Through the overall planning and data management and control of data, combined with the technical components of the middle office, the enterprise market operation department provides integrated data operation closed loop from customer data collection, analysis to application execution, and provides multi-level and multi-dimensional data asset services to the business . The construction of the middle station includes the creation of five major capabilities: data collection capabilities, data storage integration capabilities, data application capabilities, data governance capabilities, data operation capabilities, etc.

Platform Function

Ruihedata focuses on "platformization", "assetization" and "serviceization", focusing on digital intelligence scenarios, empowering the industry ecology, and letting data generate value

Data collection & Migration capabilities

Heterogeneous data conversion, file compression, protocol encapsulation and flow control, etc., for the calling scene of the underlying data

Storage Integration

Integrate the existing data platform and data assets in the data lake, establish a data asset management system, and provide data support

Data Application

Provide API registration, API query HIVEORACLEREDIS and other data ad hoc query component support; open multi-tenant based on data assets to provide mining tools for data innovation research and development

Data Governance

Provide data dictionary management (business dictionary, technical dictionary) and publish data standards based on metadata, monitor the deviation of metadata and data standards to correct data quality

Data Operation

Analyze data usage, detect data usage costs and processing paths, divide data into hot and cold regions, optimize platform-level system capabilities, and ensure service quality

Digital Strategy

Data · Service

Platform Advantage

Platform Advantage

Decoupled modular design of lightweight components

According to the current construction foundation and construction situation, transform as needed to maximize the protection of existing platform construction assets

Open technology ecology

Can be customized and compatible with related technical components to break through technical barriers

Adapting to innovation-driven rapid changes

Break the technical framework of tightly coupled technology and business, and reduce the business impact of changes in the underlying technology platform

Platform Value

Platform Value

Fast response to massive data

Quick response to massive data, multi-scenario data query response capability

Free up more capacity

Quickly integrate data assets for applications, reduce repeated development and release technological capacity

Open innovation environment

Promote digital innovation and improve the friendliness of business and data use by data personnel

Unified business export

Improve data quality and reach a unified data processing caliber and logical rules

Experience it now and start the journey of digital transformation !