摘 要
随着信息技术的迅猛发展，大数据平台在各领域的应用日益广泛，但数据质量、安全性和合规性问题也愈发凸显。为解决这些问题，本研究聚焦于大数据平台的数据治理策略与实践，旨在构建一套系统化、规范化的数据治理体系，以提升数据资产的价值和可用性。通过文献综述、案例分析及实证研究相结合的方法，深入剖析了当前数据治理面临的挑战，包括数据孤岛现象严重、数据标准不统一、隐私保护不足等，并提出基于元数据管理、数据质量管理、数据安全管理、数据生命周期管理和数据共享机制五大核心模块的综合治理框架。该框架创新性地引入了智能化技术，如机器学习算法用于异常检测，区块链技术保障数据溯源与不可篡改，实现了从数据采集到销毁全生命周期的有效管控。研究结果表明，所提出的治理策略能够显著提高数据准确性、一致性和安全性，降低数据管理成本，增强企业竞争力。本研究的主要贡献在于提供了一套可操作性强且适应不同行业需求的数据治理解决方案，为推动大数据产业健康发展提供了理论依据和技术支持。
关键词：大数据治理 数据质量 数据安全
Abstract
With the rapid development of information technology, the application of big data platforms across various fields has become increasingly widespread. However, issues related to data quality, security, and compliance have also become more prominent. To address these challenges, this study focuses on data governance strategies and practices within big data platforms, aiming to establish a systematic and standardized data governance system that enhances the value and usability of data assets. By integrating literature review, case analysis, and empirical research, this study thoroughly examines the current challenges faced in data governance, including severe data silos, non-uniform data standards, and inadequate privacy protection. It proposes an integrated governance fr amework based on five core modules: me tadata management, data quality management, data security management, data lifecycle management, and data sharing mechanisms. This fr amework innovatively incorporates intelligent technologies such as machine learning algorithms for anomaly detection and blockchain technology to ensure data traceability and immutability, achieving effective control throughout the entire data lifecycle from collection to destruction. The research findings indicate that the proposed governance strategies can significantly improve data accuracy, consistency, and security, reduce data management costs, and enhance corporate competitiveness. The primary contribution of this study lies in providing a highly operational and adaptable data governance solution that meets the needs of different industries, offering theoretical support and technical assistance for the healthy development of the big data industry.
Keyword:Big Data Governance Data Quality Data Security
目 录
引言 1
1大数据平台治理的理论基础 1
1.1数据治理的概念与内涵 1
1.2大数据平台的特点分析 2
1.3治理策略的理论框架 2
2数据质量管理策略 3
2.1数据质量评估指标体系 3
2.2数据清洗与预处理方法 3
2.3数据质量监控机制建设 4
3数据安全与隐私保护 5
3.1数据安全风险识别 5
3.2安全防护技术应用 5
3.3隐私保护合规措施 6
4数据治理实践案例分析 6
4.1治理模式的选择与实施 6
4.2成功案例的经验总结 7
4.3实践中的挑战与应对 7
结论 8
参考文献 10
致谢 10
