603 words, 2.2 minutes read. By Gerard Blokdyk
Data Governance 1 big thing: Translate business requirements to project plans, organization design and service management.
The big picture: Serve as a liaison between Business and Functional areas and IT to ensure that data related business requirements for the protection of sensitive data are implemented leveraging data governance tools and best practices.
Why it matters: Work with the team and establish/update storage engineering standards and best practices that best fits in the storage automation framework for both public and private (on-premise) cloud storage platforms.
Be smart: Be confident that your personnel works closely with the CDO and other business leaders to evangelize enterprise data sharing and collaboration and to promote the enterprise wide use of data and analytics.
Meanwhile: Liaison so that your group collaborates with source systems data stewards, system owners and technical personnel for data governance and resolves any data quality or technical issues related to data ingestion.
Go deeper: Analyze, troubleshoot, and investigate security related, information systems anomalies based on security platform reporting, network traffic, log files, host based and automated security alerts.
Yes, but: Coordinate identify and record improvement plans to increase DG maturity across the business, oversight to ensure artefacts and/or processes are embedded and auditable.
Between the lines: Assure your strategy develops and implements policy and program guidance which supports the integration and synchronization of data stewardship across functions, including leading the development of business rules for capturing, sharing, using, and transferring data.
The backdrop: Organize and implement policies, procedures, structures, roles, and responsibilities that outline and enforce rules of engagement, data governance, decision rights, and the accountabilities for the effective management of information assets.
What we’re hearing: “Liaison so that your workforce develops enterprise standards and policies around data modeling, data quality and data profiling techniques to provide integration and consistency of data.“, Manager Data Governance
How it works: Define key performance indicators for quality, compliance metrics to ensure data related policies and standards are adhered to and provide a data governance scorecard.
The bottom line: Create and maintain a data governance framework that establishes roles and responsibilities for data governance and decision making to meet the enterprises data objectives and goals.
What’s next: Liaison so that your organization is involved in vulnerability and compliance assessment tools, data governance and compliance frameworks such as HIPAA, SOC2, ISO 27001, ISO 27018, NIST 800-171 and 800-53, FedRAMP, HITRUST and PCI DSS.
ICYMI: Assess the performance of plant Data Coordinators in meeting business needs and data quality requirements and work with Master Data Coordinators and the supervisors to address performance issues.
Look inside the Data Governance Kanban:
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