664 words, 2.5 minutes read. By Gerard Blokdyk

Data Governance 1 big thing: Consider complex industry specific business concepts with executives, line managers and data scientists.

The big picture: Ensure data and tech centered tools and platforms at your organization are set up strategically to benefit all verticals and implement a data governance policy in collaboration with the business verticals.

Why it matters: Roll out an enterprise wide data governance framework, with a focus on continuous improvement of quality and protection of sensitive data through modifications to organization behavior policies and standards, principles, governance metrics, processes, related tools and data architecture.

Under the hood: Elevate awareness and educate business owners on enterprise data quality initiatives, including data governance, data policy, master data and metadata management, and data quality.


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Go deeper: Verify that your group is willing to create new processes for better governance and not shy to make necessary changes to operational model for improved efficiencies.

The backdrop: Ensure you have a detailed data management skillset including data governance, standards management, data structures, modeling, and complex data relationships (including structured and unstructured data).

State of play: Lead in creating the information/data governance architecture required to oversee (internal) customer business requirements, design and development of information and data governance solutions.

Be smart: Ensure your data practitioners are involved in a wide range of activities, ranging from data modeling, database/ETL development, data analysis, BI development and data governance.

What we’re hearing: “Be confident that your workforce supports renewal opportunities by assessing the health of a contract and the likelihood of cancellation (account status, tracking, and communication with stakeholders)., Senior Manager IT Service Management Office

Between the lines: Foster replace supports (internal) customer Domain Owner in the establishment of (internal) customer master data management, data governance and data quality frameworks and processes.

What to watch: Support the Finance Data Governance Steering Committee, comprising resources from Finance, the Business and other Corporate Functional areas, to achieve their objectives; resolve issues escalated from data governance representatives on the Finance Data Working Group.

Meanwhile: Secure that your company collaborates with the Data stewards, data custodians and report developers to ensure consistent use of data definitions, authorized data sources, and calculations.

On the flip side: Liaison so that your organization is responsible for all aspects of data governance, developing the overall data architecture strategy, creating and maintaining standards and best practices for data provisioning and data integration, enterprise data modeling and design.

The bottom line: Make sure your workforce is working with stakeholders on teams including Technology, Engineering, Data Science, Product Management to develop, influence, and facilitate cross-functional personal information data governance practices and programs.

What’s next: Confirm that your personnel is involved in any of the following disciplines/technologies is an advantage: data and analytics solutions, metadata management solutions, data governance, stewardship, data categorization taxonomy and ontology models, data classification, data integration.

ICYMI: Conduct business information modeling: Create and manage business information models in all the forms, including conceptual models, relational database designs, message models and others.

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