Be accountable for creating Data Quality scorecards on various attributes to grade the source data to the golden record (completeness, accuracy, duplication, consistency, conformity, integrity), and data analyst tool allows data stewards to choose components, create and refresh scorecards.

More Uses of the Data Quality Toolkit:

  • Gather and identify business requirements and data sources, working closely with business partners and business analysts to determine quality expectations.
  • Analyze and validate real world data, work with engineering and product management teams to design solutions to improve Data Quality.
  • Audit: implement key business processes, recommending areas for improvement, and lead defined projects to enhance the overall sales quality.
  • Confirm your organization ensures quality standards are established in accordance with internal practices, risk and compliance policies and procedures, and regulatory requirements.
  • Support the data governance function and lead various activities implementing policies, processes, standards and technology.
  • Systematize: research and recommend machine learning and artificial intelligence techniques for delivering actionable insights and to create accurate predictions.
  • Develop processes and best practices to facilitate engagement with the key stakeholders and translate business requirements to functional data requirements.
  • Facilitate collaboration with technical counterparts to ensure seamless integration of technical and functional teams to deliver big data for your organization.
  • Arrange that your organization develops operational controls for the monitoring and detection of Data Quality issues and develops continuous Data Quality improvement processes.
  • Improve Data Quality and fix data issues in dashboards, reports, data warehouses, operational data stores and other disparate data sources.
  • Establish that your organization directs, lead and motivates cross functional team members in strategy development and day to day planning and execution of Quality auditing processes and procedures.
  • Manage work with it to establish, monitor and maintain data etl processes and provide support for enterprise data warehouse and reporting platforms.
  • Assure your organization demonstrates initiative in identifying opportunities for self development and enhancement of current expertise and maintains proven skills as evidenced by Data Quality collection and productivity review.
  • Establish that your organization demonstrates skill in data analysis and techniques by resolving missing/incomplete information and inconsistencies/anomalies in routine research/data.
  • Lead technical expertise in modern Client Digital Engineering and associated technologies, cloud platforms, Data Quality, governance and architecture.
  • Manage work with lines of business to identify and solve data integrity and quality issues, recommend Data Quality improvement opportunities, and to establish new metrics for tracking performance of critical data elements.
  • Drive development of domain and divisional adoption plans to expand the Data Quality Monitoring coverage and track progress against it.
  • Support divisions and business functions in terms of integration with the Group Data Quality Monitoring platforms and adoption of group standards and best practices.
  • Warrant that your organization provides direction to teams across the enterprise regarding the development and implementation of the information management strategy to support the measuring and monitoring of enterprise business needs.
  • Establish and maintain an ongoing process for reviewing suspect data, determining root cause, and communicating remediation requirements.
  • Develop and support initiatives in cross functional teams that ensure accurate data sources and improve systems to optimize workflows.
  • Establish that your organization monitors internal feedback mechanisms for reporting on Data Quality issues to assess the potential for larger Data Quality issues.
  • Acquire data from primary or secondary data sources and maintain databases/data systems to empower operational and exploratory analysis.
  • Ensure you respond to system failures; analyze and resolve underlying problems; perform virus security operations, distribute software over the network or other similar operations.

 

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