730 words, 2.7 minutes read. By Gerard Blokdyk
Data Governance 1 big thing: Assure your personnel is involved in Data Governance around lineage, quality, catalog etc.
The big picture: Certify your workforce is contributing to the continuous learning mindset of your organization by bringing in new ideas and perspectives that stretch the thinking of the group.
Why it matters: Lead a team of data governance analysts to drive execution of Data Governance and Enablement program in line with changing environment, regulations and risks.
On the flip side: Work with business SMEs and identified project stakeholders to develop requirements (functional/non-functional/operational/data quality) for Metadata Management system and Data Governance Center application.
Be smart: Define and implement a data governance program that outlines the guiding principles for how the organization acquires, transforms, accesses, and uses data allowing for traceability from business goals down to services and key performance indicators for measuring the results of data services.
Go deeper: Work with the employees manager to continue to identify areas of improvement, additional audits, and potential additional systematic measurements to be implemented by Dodge Content.
How it works: Identify critical metrics to understand the performance of the ongoing processes and new initiatives, develop reporting dashboards to track progress, and ingrain these metrics into teams day-to-day decision-making.
Between the lines: Guarantee your strategy is responsible for leading data governance and strategy as it relates analytical data and insights to support key business decisions.
State of play: Assure your operation designs and builds modern data environments that are comprised of both raw data stores and cleansed data repositories (internal and external sources) and are populated by a combination of batch and streaming data pipelines for the purpose of optimizing the delivery and performance of advanced analytics and predicative models.
Yes, but: Make sure the Master Data Management Data Governance consultants responsibilities which need to be in place include helping (internal) customers with strategy definition, project implementation, configuration, maintenance, and guidance on best practices for MDM and Data Governance initiatives.
What to watch: Develop experience building complex distributed data management infrastructure integrating data from multiple sources, including the flexibility to add new sources as the business environment changes.
The backdrop: Deliver and execute a plan to modernize the Risk/Quality project data infrastructure and tools to efficiently support project operations, reporting, and analytics.
Meanwhile: Provide strategic leadership toward the development of a data platforms, capability roadmaps, business alignment, data processes, data policy management, data architecture, data quality, and data integration.
What we’re hearing: “Secure that your organization is understanding and involvement in data (data management, data analysis, data governance, ETL processes, database principles, SQL, data security, data stewardship or any combination).“, Data Modeling Manager
The bottom line: Safeguard that your personnel is reporting as a member of the Business Intelligence Services team, the Enterprise Business Intelligence and Data Governance Analysts is responsible for undertaking multiple engagements, working with different teams and business stakeholders, focusing on multiple aspects of business intelligence, data governance, data quality, and data initiatives/projects.
What’s next: Understand the key business deliverables required for a Program/Project and the associated dependencies on other programs to ensure all dependencies are actively managed.
ICYMI: Participate in post mortem meetings and report out on data impacts and outages across organization in a manner which instills confidence in issue understanding, impact and next steps along with prevention/elimination recommendations.
Look inside the Data Governance Kanban:
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