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Extracting Value from Massive Data to Accelerate Intelligent Transformation

HUAWEI CLOUD FusionInsight Intelligent Data Lake has provided enterprise-class data lake solutions for over 3000 customers from diverse industries in more than 60 countries and regions. Solutions include government data governance, a unified portal for all government services, real-time financial risk control, integration of business, operations, and management support systems for carriers, smart campuses for large enterprises, smart urban rail, and smart airports.

HUAWEI CLOUD FusionInsight offers a suite of cloud services that are instrumental to a wide range of data analytics scenarios, including MapReduce Service (MRS) for cloud-native data lakes, Data Warehouse Service (DWS), Data Lake Governance Center (DGC), and Graph Engine Service (GES). Scenarios include real-time analysis, offline analysis, interactive query, real-time retrieval, multimode analysis, data warehouse, data mart, data access and governance, and graph computing. In short, the true value of data is finally unleashed, with one lake for one enterprise and one lake for one city.

Advantages

  • Ultra-High Bandwidth
    Cloud-Native Data Lake

    • Elastic resource provisioning: On-demand scaling shortens the time needed for provisioning from days to minutes.
    • Unified metadata: Data Lake Catalog (DLC) provides unified metadata management and global data visualization.
    • Storage-compute decoupling: Object Storage Service (OBS) and Huawei-developed enterprise-class Erasure Code (EC) reduce Total Cost of Ownership (TCO) by over 30%.

  • Superior Performance
    Three Lakes, One Architecture

    • Logical data lake: Cross-lake, cross-warehouse, and cross-cloud collaboration efficiency improved by over 30%.
    • Real-time data lake: Millisecond Online Analytical Processing (OLAP) improves timeliness from T + 1 to T + 0.
    • Offline data lake: A warehouse within a data lake and shorter analysis links, boosting analysis efficiency by over 10x.

  • 10 fusion load
    Evolving Enterprise-Class Data Lakes

    • Openness: Embracing open source communities.
    • Convergence: Convergent batch, stream, and interactive analysis based on multiple engines, achieving over 90% resource utilization based on unified resource scheduling.
    • Large-scale: Ultra-large clusters with 20,000+ nodes and cluster federation with 100,000+ nodes are supported.
    • Reliability: Online rolling upgrades, two-site three-center high reliability, and always-on services.

Architecture

HUAWEI CLOUD FusionInsight Intelligent Data Lake enables full-lifecycle data management, covering collection, storage, computing, management, and usage. It supports the deployment of up to 20,000 nodes in a cluster, while rolling upgrades help prevent service interruptions. And, with more than 1000 refined and visualized Operations and Maintenance (O&M) metrics, cluster management is made more reliable, secure, fault-tolerant, and easy to use.


  • Huawei FusionInsight big data architecture

  • MRS

    MRS can build logical, real-time, and offline data lakes with one architecture to provide cloud-native big data solutions for both governments and enterprises. Featuring a range of components such as Spark, ClickHouse, HetuEngine, Hive, HBase, and Hudi, diverse scenarios are supported, including real-time or offline analysis, interactive query, real-time retrieval, multimode analysis, data warehouse, data access, and data governance.

    DWS

    DWS is a distributed data warehouse with analysis and hybrid load capabilities. It can handle petabytes of data, performing multimode analysis and real-time processing for a data warehouse or data mart. DWS provides real-time analysis and decision-making for hybrid load scenarios, and has been widely adopted for core analysis systems in finance, government, and telecom sectors.

    DGC

    A one-stop full-lifecycle data development and operation platform, DGC provides functions such as data integration, development, governance, service, and visualization. It also supports intelligent construction of industry knowledge libraries, and incorporates data foundations such as big data storage, computing, and analytics engines, helping enterprises quickly build out their data operations.

    GES

    Offering hyper-scale integrated graph query and analysis, GES provides more than 30 high-performance algorithms for diverse scenarios and supports the query of tens of billions of vertices and hundreds of billions of edges in just seconds. It's especially well suited for scenarios involving large volumes of relationship data, including social applications, enterprise relationship analysis, risk control, personalized recommendations, and anti-fraud applications.

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