Big Data 15 min read

How Panasonic Overcame Data Silos: A Big Data Governance Journey

Panasonic's digital transformation case study details the challenges of fragmented data across 64 subsidiaries, the strategic adoption of a serverless big‑data platform, governance milestones from 2021 to 2023, tool comparisons, standardization efforts, talent development, and future outlook driven by five core values.

Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
How Panasonic Overcame Data Silos: A Big Data Governance Journey

Panasonic's Digital Reform Challenges

Panasonic Group operates 64 legal entities in China and Northeast Asia with about 40,000 employees. Its diversified businesses—R&D, manufacturing, sales, services—create complex supply‑chain and management challenges, especially in the digital era.

Data Governance Goals

To improve operational efficiency and achieve “excellence operation”, Panasonic aims to break silos across its 64 subsidiaries, unify eight business scenarios, and build a global‑optimal digital model.

Governance Timeline

2021: Established a unified regional big‑data platform.

2022: Standardized data metrics, performed data asset inventory, and began product‑level data services.

2023: Obtained software copyright for a manufacturing‑focused data middle‑platform and launched a Data Analysis Academy.

Future: Focus on intelligence, platformization, and integration.

Architecture Selection – Low‑Cost, High‑Performance Serverless

Panasonic evaluated two solutions: Alibaba Cloud’s fully managed PaaS (DataWorks + MaxCompute) and a competitor’s IaaS‑based offering. The PaaS option was chosen for its zero‑maintenance serverless architecture, strict permission control, and multi‑tenant support.

Tool Comparison

Alibaba Cloud DataWorks provides a unified user authentication, visual configuration, fine‑grained permission management, and fully managed resources, reducing operational overhead. The competitor’s product lacked open APIs, had limited concurrency, and required extensive manual maintenance.

Agile Innovation and Standardization

Standardizing business metrics across subsidiaries eliminated inconsistent inventory definitions, enabling unified reporting for senior management. A common data model (DWD, DWS) and shared data services increased reuse and reduced platform costs by 30%.

Talent Development

Panasonic launched a Data Analysis Academy offering courses on data analysis, big data, and algorithms to employees across its 64 subsidiaries. Within a month, 52 subsidiaries participated, addressing the skill gap in data‑driven decision making.

Future Outlook

Panasonic’s five core values—look outward, simplify, collaborate, challenge, grow—guide its ongoing digital transformation, emphasizing continuous strategic adjustment, technology adoption, and cultural change.

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Big Datacloud computingData PlatformDigital TransformationData Governance
Alibaba Cloud Big Data AI Platform
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Alibaba Cloud Big Data AI Platform

The Alibaba Cloud Big Data AI Platform builds on Alibaba’s leading cloud infrastructure, big‑data and AI engineering capabilities, scenario algorithms, and extensive industry experience to offer enterprises and developers a one‑stop, cloud‑native big‑data and AI capability suite. It boosts AI development efficiency, enables large‑scale AI deployment across industries, and drives business value.

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