663 words, 2.5 minutes read. By Gerard Blokdyk
Data Governance 1 big thing: Design end to end analytic framework, including overall architecture, capabilities, platforms, tools & governing processes.
The big picture: Be confident that your strategy leads complex enterprise wide programs and collaborates on strategic initiatives for data governance, data quality and metadata activities.
Why it matters: Make headway so that your design promotes the data warehouse process, outcomes and results to your organization, which includes the enterprises IT and business leaders.
On the flip side: Make headway so that your strategy is involved in data governance principles, related standards and providing direction for development of process, procedures, controls.
Be smart: Update ensures that the execution and implementation of Data Governance policies and processes are in line with corporate strategy and corporate process frameworks.
Meanwhile: Make sure the Data Governance Manager provides oversight for solutions to secure data including Data Classification, Data Loss Prevention (DLP) for structured and unstructured data.
How it works: Determine and enforce specific security and privacy requirements for each piece of data especially as it relates to privacy laws, industry regulations, and corporate compliance mandates.
What they’re saying: “Confirm that your company works with business units and corporate/technology functions across the enterprise to support development, socialization, and execution of data management strategy as well as to enable business and product via appropriate management and use of data.“, Data Modeling Manager
Under the hood: Work closely with business owners, product owners, and related applications to ensure requirements are interpreted correctly in detailed design specifications and in the data integration implementations.
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Go deeper: Serve as business liaison during reorganizations to ensure that data is updated timely and managed properly through incorporation in downstream systems across your organization.
The backdrop: Work with peers in the Data Governance group to operationalize shared services for property, client, and other master data management, including improving integration with other contributing data sources, and optimizing data sourcing and migration tasks.
Yes, but: Make sure the focus is on Data Governance, working across cross functional teams to ensure adherence to process and continuously improve the system of record.
State of play: Standardize for managing responsibility of the ongoing identification of the organizations data and analytics needs to deliver and expand capabilities across business intelligence, forecasting, prediction, and optimization that ultimately enhance your organizations performance and success.
What to watch: Ensure that the data used follows the compliance, access management and control policies of your organization while meeting the data governance requirements of the business.
The bottom line: Guarantee your group is managing teams implementing Data Governance tools with a complex business environment, through requirements gathering, building, testing, and production roll out.
What’s next: Assure your process is involved in gathering and creating analytic business requirements, researching potential data sources (both internal and external sources), designing, developing and maintaining data assets.
ICYMI: Guarantee your group organizes, coordinates and assists cross functional teams in planning, development, and execution of Data Governance oriented business processes at the operational level.
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