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  • Financial Data Analysis Storage Solution

    Financial Data Analysis Storage Solution

    Unlock the full value of your data and move toward the convergence of big data and AI.

  • Overview
  • Architecture
  • Benefits
  • Related Products
  • Case Studies

Financial Data Analysis Platform: Power the Next Wave of Growth

Financial data analysis platforms are now the driving force of banking, fueling new services such as precision marketing and digital risk control. For traditional storage-compute coupled solutions based on native Hadoop, that's a big problem given their limited scalability, low resource utilization rate, and lack of support for cross-region mobility. In short, in the age of artificial intelligence (AI), such solutions are already badly out-of-date.

And the answer? Huawei's Financial Data Analysis Storage Solution uses professional scale-out storage and decoupled storage-compute architecture to deliver remarkable cost-efficiencies, robust reliability, and effortless scalability. With support for Simple Storage Service (S3) and Hadoop Distributed File System (HDFS) protocols, this solution seamlessly interconnects with mainstream big data platforms, empowering enterprises to easily evolve toward AI data lakes and effectively accelerating the financial industry's journey toward data-AI convergence.

Architecture

Architecture

Architecture
Huawei

Benefits

Storage-Compute Decoupling for Lower TCO

Storage-Compute Decoupling for Lower TCO

Decoupled architecture: On-demand resource expansion.

Elastic erasure coding (EC): 1.75x higher resource utilization than the multi-copy method.

2 U, 36-slot high-density hardware: 1.5x higher slot density than mainstream industry offerings.

High Data Security and Reliability with Zero Data Loss

High Data Security and Reliability with Zero Data Loss

Multi-active setup across 2–12 sites with cross-site EC.

99.9999% reliability, RPO = 0, and visibility and availability of remote data.

Convergence of Data Lakes, Warehouses, and AI for Seamless Evolution

Convergence of Data Lakes, Warehouses, and AI for Seamless Evolution

Unified data format, allowing one copy of data to be shared by multiple workloads.

Effortless scale-out and smooth evolution.

Case Study

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