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Improving data management and governance

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Data management and governance requires a systematic approach for success. To start, the approach should include policies for data onboarding, validation, normalization, classification, and enrichment. It must also define policies for data retention, lifecycle management, and stewardship. When you pair these policies with clearly-defined roles, responsibilities, processes and tools, your framework increases the chances that you'll achieve robust data reliability, compliance, and optimized utilization. The strategies provided in this pathway will help you accomplish these goals. You can work through them sequentially or in any order that suits your current level of progress.

This article is part of the Improve Performance outcome. For additional pathways to help you succeed with this outcome, click here to see the Improve Performance overview.

Improving data management and governance
Pages: 3
  • Following data onboarding best practices
    Implementing standardized data onboarding procedures in the Splunk platform ensures that data is ingested and managed consistently.
  • Establishing data retention policies
    Good data retention is about striking the right balance between resource utilization, data availability for analysis, and compliance with internal and external regulations.
  • Creating a data governance framework
    A governance framework provides clarity in data-related roles and responsibilities, ensures adherence to organizational and regulatory standards, and mitigates risks associated with data anomalies or breaches.

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