720 words, 2.7 minutes read. By Gerard Blokdyk
Data Governance 1 big thing: Work closely with internal stakeholders to implement and embed privacy by design principles.
The big picture: Oversee site compliance with the Quality Management System and regulatory requirements pertaining to data governance, including the development of indicators that monitor data governance processes and performance at the Site level.
Why it matters: Support Data Governance as a data steward/custodian by defining KPIs for measurement analysis, maintaining measurement and analysis repository, updating data definitions and metadata, defining data standards, and monitoring data quality.
What to watch: Be a focal point of contact for stakeholders throughout the analytics project lifecycle, and work with internal and external partners to design, validate, and deliver solutions with a commercial benefit for the organization.
On the flip side: Establish that your process is leading development and realization of strategic and tactical data initiatives like migration, data quality, data governance and integration as well as data warehouse design, modeling and implementation for your (internal) customers.
The backdrop: Partner with Service teams to ensure service parts are loaded in various data portals and monitor to assure standards are loaded and costed in ERP systems.
What they’re saying: “Assure your operation is responsible for leading the implementation of the data integrity culture and strategy and data governance framework and processes for the site and ensuring compliance with all applicable regulatory requirements at the system level.“, Data Governance Specialist
Under the hood: Work with peers in the Data Governance group to operationalize shared services for property, (internal) client and other master data management, including improving integration with other contributing data sources, and optimizing data sourcing and migration tasks.
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Be smart: Lead working sessions with operational and information system owners on the onboarding of new data assets including documentation of processes, procedures, system interfaces, data dictionaries, data models and requirements for all new analytical data assets.
How it works: Make sure your personnel designs data governance and inventory management programs that cover aspects of data management including, data quality, master data management, meta data management, data project portfolio management.
Yes, but: Make headway so that your staff is involved in or exposure to one or more data management disciplines as data quality, data governance, MDM, databases, ETL, data migrations, BI, reporting, data lakes, big data, cloud ecosystems.
Between the lines: Develop and build strong working partnerships and strategic relationships with key partners across the business and technology in aligning implementation and operational strategies.
Meanwhile: Partner with key stakeholders in Geographies, Demand and Supply Planning, Operations, Logistics, Security, Technology and Analytics functions to execute data governance and quality priorities.
Go deeper: Ensure you help (internal) customers minimize public cloud security and compliance risk by providing real time visibility into misconfigurations, threats, resource relationships, and associated risks.
The bottom line: Assure your process capabilities supported include (internal) customer matching, preferences, profile, interactions, contact points, householding, marketing campaigns, enterprise metrics, (internal) customer data governance, and adoption of new solutions.
What’s next: Build a self service reporting platform to sustainably support the long term data needs of your organization, while managing ad hoc reporting requests.
ICYMI: Work with Domain Stewards and Curators to ensure that data related business requirements for protecting sensitive data are clearly defined, communicated and well understood and considered in the context of operational prioritization and planning.
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