BIG DATA

Capabilities & Features

data Integration

Data integration serves as a tool for consolidating heterogeneous data. It supports hundreds of heterogeneous data sources, including structured, semi-structured, and unstructured formats. It provides full graphical interfaces for batch collection, whole-database migration, and real-time acquisition modes. By leveraging intelligent generation technology for heterogeneous data aggregation tasks, it automatically creates data collection workflows based on source types.

Data development

Data development is a tool for processing massive data. It supports over hundreds of structured data types and features built-in high-performance data processing operators to enhance efficiency. The product enables full-process visual drag-and-drop operation development, lowering the technical threshold for developers.

Data reconciliation

Data reconciliation is a tool for asset comparison between data sources. It provides full WEB operation mode, supports structured and unstructured data reconciliation, and provides wizard-style guidance to create reconciliation tasks.

Workflow orchestration

Workflow is a tool for orchestrating automated workflows. It supports the arrangement of complex DAG tasks and provides real-time visual monitoring of task execution status. With preset SQL, stored procedures, Spark, Shell, Python, HTTP, subtasks, and dependent task nodes, it enables sophisticated data analysis and processing through configuring inter task dependencies and linking workflows with scripts.

Data Operations

Data Operations and Maintenance (DOM) is a unified tool for monitoring, scheduling, and managing operational tasks. It provides services including task monitoring, data analytics, and maintenance alerts. Centralized task management reduces operational labor demands, while intelligent scheduling help optimize resource allocation by balancing peak and off-peak periods. Customizable alert rules enable maintenance teams to promptly identify anomalies, significantly simplifying the operational process.

Competitive Edge

Intelligent Data Acquisition Capability

Supports automatic generation of data collection tasks, which greatly improves efficiency compared with manual configuration or script development. Application scenarios:flow processing & analysis in the financial industry

Multi-engine data processing

An efficient big data processing engine, which supports distributed computing and parallel loading technology, and realizes reasonable allocation and optimal utilization of resources by setting up computing allocation for tasks.

Powerful Scheduling Engine

Provides a powerful distributed scheduling engine, supports complex job flow orchestration, supports efficient operation of data processing tasks, and offers guarantee for massive heterogeneous data integration.

Powerful and Flexible Data Access capabilities

It supports hundreds of multi-source heterogeneous data access, including relational database, MPP database, big data platform, NoSQL, text, connection book, interface, etc. For new data sources and data types, it supports online dynamic adaptation.

Full Graphical Data Development

It has a graphical data development environment, which can complete the design of complex data processing process by drag and drop, reduce manual coding, lower the difficulty of data development, and comprehensively improve the efficiency of data development.

Resume Transmission

Supports various data extraction modes, supports break points transmission regardless of file or database, and can ensure that tasks run smoothly in the process of file or data transmission due to network anomalies, data anomalies and other scenarios.

Cross-platform Adaptation Capability

It has the ability to adapt across vendors and platforms, and fully supports the deployment and installation of domestic operating system Kirin and domestic chips such as Loongson, Zhaoxin, Kunpeng and FeiTeng.

Real-time Data Processing Capability

It supports real-time collection and processing of application-level message queues and Kafka message streams, and can simultaneously meet the requirements of high speed, high reliability and massive data processing.

Application Scenario

Electronic government scenarios

The ETL component collects business data from each authority department The integration and analysis of the real needs of the masses are found, and the application function of data prediction is strengthened to promote the government to take more humanized, convenient, targeted and effective measures.

Learn more Free trial

Financial industry application scenarios

Collect fund transaction data based on ETL component · Real-time capital flow: collect capital flow in key areas, capital flow in key industries, frequent and similar amount of capital flow, seasonal capital flow, holiday capital flow, occasional large capital flow. ·Data-Enabled Credit Risk and Control Enhancement: By integrating big data sources including P2P platforms, micro-lending institutions, credit bureaus, banks, third-party payment providers, and big data network, we connect diverse scenarios to collect real-time data from virtual economy networks and e-commerce platforms. Through decentralized distributed query mechanisms, this approach breaks down information silos that create data gaps within industries, enabling efficient risk management.

Learn more Free trial

Transportation industry application scenarios

Leveraging SDC ETL's robust capabilities for multi-source heterogeneous data integration, the project has successfully aggregated and integrated dozens of data categories, including airport flight operations, flight path maps, aircraft stands, passenger information, and baggage data. By implementing efficient data access solutions, it effectively met critical challenges such as fragmented underlying data in user information systems, integration barriers of real-time data streams, and access limitations for critical data resources.

Learn more Free trial

Enabling converged multi-source data processing, breaks down information silos, and unlocks big data value.

SDC ETL Data Integration Software

Capabilities & Features

data Integration

Data development

Data reconciliation

Workflow orchestration

Data Operations

Competitive Edge

Intelligent Data Acquisition Capability

Multi-engine data processing

Powerful Scheduling Engine

Powerful and Flexible Data Access capabilities

Full Graphical Data Development

Resume Transmission

Cross-platform Adaptation Capability

Real-time Data Processing Capability

Application Scenario

Electronic government scenarios

Financial industry application scenarios

Transportation industry application scenarios

User Benefits

Distributed Computing for Massive Data

All Types of Data are Stored Uniformly