Use Case Intelligence RSS Search use cases Search
Tencent Cloud Media and Entertainment China Translated from Chinese

China Media Group (Yangshipin)

Data Lake / Data Warehouse Modernization · Real-time Analytics

Yangshipin needed a secure, data-driven media architecture that could unify user, content, and production data while supporting large-scale video distribution, AI-assisted production, and 5G-era media operations.

Read the original story Explore all use cases
The dedicated cloud environment uses two availability zones for disaster recovery.
The platform processes hundreds of millions of data items each day.

Reported impact

Business outcome

Yangshipin gained a governed media data platform that improves content quality, operational coordination, AI-assisted production, and security for a national-scale video service.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

China Media Group's Yangshipin platform uses Tencent Cloud as the data and capability backbone for a national 5G new-media service. Tencent built a hybrid-cloud base with public, dedicated, and private cloud resources, and the dedicated environment uses two availability zones for disaster recovery. On top of that foundation, Yangshipin runs a capability middle platform composed of a video middle platform, AI middle platform, and big-data platform. The system ingests client behavior, user data, media assets, production-system data, and internet trend data, then applies unified governance, warehousing, analytics, recommendation, storage, transcoding, content review, intelligent clipping, and smart cover generation. Client apps, creator accounts, content operations, and security controls all consume these shared services. The result is a data-driven media architecture where content production, distribution, and operations all draw from one governed platform instead of isolated systems.

Data flow

Client behavior, user, media-asset, production, and internet trend data flow into the big-data and data-middle-platform layers, where governance, storage, recommendation, analytics, and AI services feed content operations, creator workflows, apps, and reporting across the Yangshipin ecosystem.

Solution architecture

5 components · 4 layers
  1. Compute
    • AI Middle Platform Adds intelligent services such as content review, smart clipping, and recommendation support.
    • Big Data Platform Processes and analyzes large volumes of audience, content, and production data.
  2. Serving
    • Video Middle Platform Supplies shared video storage, transcoding, review, and editing capabilities.
  3. Orchestration
    • Hybrid Cloud Foundation Provides the public, dedicated, and private cloud base for resilient new-media operations.
  4. Governance
    • Data Middle Platform Defines the unified data-governance model and shared data services for the business.

Architecture clues

  • Shared services include storage, transcoding, moderation, smart clipping, recommendation, governance, and analytics.
  • The architecture explicitly follows a large middle-platform plus small front-end pattern.
  • The hybrid-cloud foundation spans public cloud, dedicated cloud, and private cloud resources.

Evidence from the source

Tencent provided a reliable, secure, and easy-to-use big-data platform for Yangshipin that processes hundreds of millions of data items every day and supports an all-data-into-the-middle-platform architecture. (original: 腾讯基于多年海量数据处理经验，为“央视频”5G新媒体平台提供可靠、安全、易用的大数据平台，每天处理几亿的数据，实现了“全部数据接入中台、全部数据从中台提供”的大数据架构。)
The capability middle platform includes the video middle platform, AI middle platform, and big-data platform, and provides video storage, transcoding, moderation, intelligent editing, data governance, analytics, and recommendation. (original: 能力中台包含视频中台、Al中台、大数据平台，提供视频存储、编解码、标准化、内容审核、智能剪辑、智能封面、数据采集、数据治理、数据分析展示、智能推荐等能力。)
The hybrid-cloud base uses a public-cloud plus dedicated-cloud plus private-cloud model, and the dedicated cloud uses two availability zones for disaster recovery. (original: 混合云基础底座采用公有云+专有云+私有云的混合云模式，专用云的两个可用区进行业务容灾。)
The technical architecture uses a large middle platform plus small front ends and includes a hybrid-cloud base, capability middle platform, business front end, client, account platform, and network security. (original: 在整体技术架构设计上采用先进的“大中台+小前台”理念，含混合云基础底座、能力中台、业务前台、客户端、央视频号、网络安全六部分。)
Transparency Evidence & methodology 75/100 reference value · 77% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value75/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence77%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Tencent Cloud

    China Media Group (Yangshipin) customer story

    First-party
    https://cloud.tencent.com/customer/yangshipin
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

Related

Similar use cases

See all like this
Databricks Apr 23, 2026 Amagi Media and Entertainment Global Amagi supports 8,000+ streaming channels, 300+ distributors, and 26B annual ad impressions for 45% of the world's top media companies, but its legacy stack (Dataproc for batch, Snowflake for analytics, in-house… 15x faster time to market for new data products Data Lake / Data Warehouse ModernizationReal-time Analytics Databricks Genie · Databricks SQL · Databricks Serverless Compute Google Cloud Archived · Apr 13, 2026 Class Editori Media and Entertainment Italy With global giants like Google, Amazon, and Netflix setting new standards for personalized content delivery, Class Editori recognized that consumer habits were shifting toward conversational interfaces. Converted trial users into paid subscribers and secured B2B enterprise agreements Data Lake / Data Warehouse ModernizationMarketing Personalization BigQuery · Cloud Run · Gemini Databricks Apr 3, 2026 SūmerSports Media and Entertainment United States SūmerSports helps NFL and college football teams make multimillion-dollar roster decisions by aggregating 14 data sources (player tracking, scouting, client data, NFL contracts) at up to 200TB per season. Its… 14 data sources aggregated Data Lake / Data Warehouse ModernizationReal-time Analytics Agent Bricks / Mosaic AI · Databricks AI/BI · Databricks Asset Bundles