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Master Data Management 1 big thing: Manage product market profitability through mix price management and establishing internal product cost goals.
The big picture: Safeguard that your process establishes monitoring criteria and monitoring plans to ensure the educational effectiveness and progress of assigned programs, and to determine compliance with Department rules and regulations.
Why it matters: Make sure your operation assesses whether data is fit for use by performing initial validation of data delivered in the context of the project.
The backdrop: Be able to translate the information architecture contribution to business outcomes into simple briefings for use by various data and analytics related roles.
Under the hood: Manage projects with touchpoints with R and D, commercial, supply chain management for new development work, ensuring adherence to master data standards and strategy.
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Be smart: Engage and interact with managers to effectively and deeply understand about the current and past Technical projects, including technologies used, development environment, and logic used.
What to watch: Interface so that your staff is involved in data warehouse design and participated in at least 1 end to end data warehouse implementation.
On the flip side: Ensure you bring together both the right knowledge and the right approach, so that they can capitalize on opportunities and deliver real results.
Go deeper: Make sure your staff 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.
Yes, but: Partner with business communities to create and drive the delivery of a prioritized roadmap for technology solutions, ensuring alignment to business strategy and considering emerging technologies.
What they’re saying: “Guarantee your team is involved in data warehousing, data architecture, ETL, MDM, database structure and design, solution performance optimization, data profiling/mining/designing/auditing, developing logical and physical data models, ensuring and maintaining data quality, technical documentation, and respective tools.“, Luis S. – Manager, Master Data Management
Meanwhile: Compile and analyze metrics and other program evaluation data, collecting data from a variety of sources, including web and social media, and presenting in a cohesive, organized format.
The bottom line: Work to place team members in roles with the right skillsets to support long term, sustainable and effective data management for the enterprise and define roles and responsibilities related to data management as well as train stakeholders on a data-driven culture.
What’s next: Make sure the corporate services and data solutions group falls under the enterprise technology and operations organization and is comprised of multiple teams focusing on various programs supporting your organization.
ICYMI: Be confident that your team provides technical expertise to the project and product team(s) to help assure that MDM solutions are designed and developed in an optimal manner and in accordance with industry and MDM best practices.
A MESSAGE FROM THE ART OF SERVICE
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