By harmonizing and cleansing your data streams, MDM paves the way for sharper analytics, enabling you to make informed decisions with unparalleled precision. Embrace the future of decision-making and fuel your business growth with the untapped potential of MDM.
Turn ideas into actionable plans with our tailored Discovery Workshops. We collaborate with your team to define goals, identify user needs, and uncover key opportunities. Through structured sessions, we create a clear roadmap, ensuring alignment and setting the foundation for a successful product development journey.
Determine key stakeholders across the organization, including IT, business units, compliance, and data owners.
Appoint a Data Governance Officer or team responsible for leading and coordinating data governance efforts.
Clearly articulate the goals and objectives of your data governance initiative, such as improving data quality, ensuring compliance, or enhancing data analytics.
Create policies and guidelines that outline the principles and standards for data management, including data definitions, lineage, and metadata management.
Ensure that these policies align with industry regulations and best practices.
Define roles and responsibilities for key data governance positions, such as Data Stewards, Data Owners, and Data Custodians.
Specify the duties and accountabilities of each role in relation to data management tasks.
Develop a comprehensive data dictionary that defines and documents data elements, their meanings, and relationships.
Ensure that data definitions are clear, standardized, and easily accessible to all stakeholders.
Deploy tools and processes to track data lineage, enabling the tracing of data from its source to its various uses and transformations.
Document data flow and transformations to enhance transparency
Establish a centralized metadata repository or catalog to store information about data assets, including data sources, schemas, and usage.
Include detailed metadata such as descriptions, ownership, quality metrics, and access controls.
Implement data quality assessments and monitoring to identify and address data anomalies, inconsistencies, or errors.
Establish data quality metrics and benchmarks.
Develop and implement procedures for enforcing data governance policies.
Ensure that data contracts, definitions, lineage, and metadata adhere to established standards.
AI & ML
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As one of the companies in the U.S.A, Tring’s advisory and consulting services understand your business requirements and help you achieve transformation based on business objectives.
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