Enterprise-level Big Data Computing

To address enterprise-level big data computing needs, we've adopted distributed data computing technology for an efficient, scalable platform.

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Technical Points and Construction Details

Here are key technical points, details, and a simplified flowchart showing how we help businesses mine data value and achieve real-time processing.

Technical Points and Construction Details

Distributed Computing Framework

Using Apache Hadoop and Spark for storage, processing, and analysis of large data. Hadoop offers a reliable distributed file system (HDFS), while Spark provides fast data processing.

Data Warehousing and Analysis

Combining traditional data warehousing methods with modern analytics tools like Amazon Redshift, Google BigQuery, or Snowflake for comprehensive data analysis and business intelligence (BI).

Real-time Data Stream Processing

Leveraging Apache Spark with Flink or Storm for real-time data stream processing, facilitating real-time data collection, processing, and forwarding.

Real-time Notification and Automation

Implementing monitoring, alerting, and automation (e.g., Apache Airflow) for real-time notification and automated responses to critical data changes.

Data Governance and Security

Implementing data governance strategies for data quality, consistency, and security, including encryption, access control, and data anonymization.

Process Overview

This framework enables enterprises to efficiently process and analyze large-scale data, swiftly address business needs, and delve into data insights and trends.

01Data Collection

Gather data from various sources, including log files, databases, third-party APIs, etc.

02Data Processing

Utilize Apache Kafka to collect and stream data to Apache Spark or Flink for real-time processing.

03Data Storage

Store processed data in HDFS or cloud storage services, forming a data lake.

04Data Analysis

Perform batch processing and in-depth analysis on stored data, leveraging data warehousing techniques to support complex queries and reporting.

05Result Application

Using analysis results for real-time notifications, automation, and decision support, this framework enables enterprises to efficiently process and analyze large-scale data, quickly meet business demands, and uncover valuable insights and trends.

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