Create charge back and cost management models to ensure the value of pay as you go model of the cloud data platform Build a DataOps platform to integrate functions that support rapid deployment and governance.

More Uses of the Metadata Toolkit:

  • Collaborate with the chief information security officers and chief privacy officers to create policies and controls for the appropriate protection of information assets.
  • Ensure you pioneer; build, maintain, optimize and update logical and physical data models along with corresponding Metadata to support new and existing projects.
  • Methodize: partner with other architects as a key interaction point for communication, evangelism, governance, and feedback into central architecture.
  • Oversee the design, implementation and on going execution of workflow processes that support the capture and maintenance of Metadata.
  • Confirm your operation analyzes and work with business and technical staff to assess existing data access and processing patterns, and designs forward thinking data architectures to meet business and technical needs.
  • Make sure that your operation creates and maintains accurate, complete and consistent governed Content, Data and Navigational Models with consistent Metadata.
  • Collaborate with data and engineering teams and project owners to establish consensus on Metadata modeling and enforce best practices.
  • Be certain that your business performs advanced data profiling, Metadata capture, data lineage, data transformation rules in support of key program deliverables.
  • Establish efficient and repeatable processes that capture system data, organize it, synthesize it, and structure the information for reporting (visualization).
  • Ensure you train; build interfaces connecting ERP and non ERP applications with data governance tool suite (MDM tools, Data Catalog tools, Metadata Management tools).
  • Secure that your strategy develops and implements short term and long term strategic goals for the Digital Asset Management system Metadata acquisition process.
  • Pilot: work closely with Standards and Practices to provide lists of upcoming content for review, and enters ratings information into multiple systems.
  • Arrange that your team assess and review new technology opportunities related to data management and impact on the enterprise data strategy and roadmap.
  • Ensure you instruct; lead the strategic direction for business information architecture, Metadata management, business data architecture, and data strategy functions.
  • Solidify in depth technical expertise regarding data models, data analysis and design, master data management, Metadata management, data warehousing, business intelligence, data quality improvement.
  • Manage IT vendor contracts, vendor risk, performance, change, and Metadata about each to provide insight into vendor usage and risks.
  • Steer: monitor regulatory guidelines compliance related guidance and emerging industry standards to determine impact on the enterprise data architecture.
  • Govern: quality assurance of all newly published or recently updated content and help conduct regular audits of older content and media to ensure formatting, Metadata, and tagging consistency.
  • Establish that your strategy performs quality control checks of the scanned images and the associated Metadata at the time of conversion, during editing, or as a review for other departments.
  • Arrange that your project uses expertise to lead efforts to identify, evaluate, and use emerging technologies in the domain of data systems that meet feasibility, performance and governance.
  • Assure your planning applies standard rules, guidelines, and reference tools and established techniques and practices; and participates in formulating plans for changes and improvements to cataloging related issues.
  • Communicate complicated technology concepts in a manner that is understandable in terms of business impact so that business decisions can be made.
  • Confirm your organization complies; focus on user efficiencies, solving business/customer issues, invent creative solutions, and ensure data accuracy across the system.
  • Audit: review and approve data designs for compliance with enterprise best practice guidelines and standards for data, Metadata, data modeling, and management.
  • Ensure data protection and create back up plan to cater to the data needs of your organization in times of emergency or Cyber attack Data Security.
  • Capture metrics and reports at the right granularity for reports and analysis to provide a big picture assessment of your organization of the analytics and data team.
  • Develop, test, and maintain high performance of your data systems to meet the requirements of the business and/clients while adhering to departmental standards.
  • Confirm your planning develops data structures for data warehouses and data mart projects and initiatives; and supports data analytics and business intelligence systems.
  • Develop: implement information and data quality management processes, data stewardship, enterprise Metadata management and related programs.
  • Collaborate with content Metadata teams to understand usage of tools and processes to assess needs, requirements and formulate technical designs and development of data.

 

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