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 analyzing tool allows Data Stewards to choose components, create and refresh scorecards.

More Uses of the Data Stewards Toolkit:

  • Establish an enterprise data catalog to ensure an accurate inventory of data assets and appropriate context to enable data analysts, Data Stewards, and other data consumers to find and understand appropriate datasets.
  • Establish consistent business processes for source data and develop business rules and data governance policies to ensure integrity and quality of your foundational data assets.
  • Communicate customer data management operational health, improvement efforts progress, and key decisions and business practices across the customer data management community.
  • Be accountable for utilizing various data sources and research methods, the Data Stewardship analyzing provides your organization and structure for Firms, organization Offices, and Contacts to be used in consolidated reporting across multiple platforms and clearing arrangements.
  • Serve as a liaison between Business and functional Product domains to ensure that data related business requirements for protecting sensitive data are clearly defined, communicated, understood, and complied with.
  • Direct: closely partner with Data Stewards to understand the needs of the business and what data relationships the models represent along with helping to identify what relationships and dependencies also need to be reflected.
  • Devise: review and update data quality rules in applications and confirm accuracy and availability of data for decision support, regulatory and financial reporting, and compliance monitoring, in coordination with business architects by data domain and Data Stewards.
  • Provide expert advice and consultation to executive management, internal departments and outside organizations to identify and research outstanding Transformation data governance issues.
  • Ensure you outpace; lead testing phase of data integration development in order to identify and remedy potential problem areas through collaboration with analysts, Data Stewards, developers, and system owners.
  • Confirm your group participates in technology development and improvement efforts to incorporate data governance consistency across systems and ensure that diverse data and data information systems users needs are accounted for as systems are developed.
  • Evaluate: work closely with it and functional area Data Stewards to create methods and procedures for identifying and maintaining critical data elements, periodic review, monitoring, troubleshooting, and resolving data quality issues.
  • Provide guidance on the creation and best practices around Data Governance, Data Stewardship and overall Data Quality initiatives and processes, as part of the overall data effort.
  • Approve system life cycle deliverables (SDLC) and activities to ensure that regulations, protocols, procedures, and methodologies are followed, and that appropriate and complete documentation is captured and reported to support validation activities.
  • Coordinate with data custodians, Data Stewards and other support teams regarding app operations, data quality in the app, data demand / consumption requirements, and open data quality exceptions / issues.
  • Direct: partner closely with business stakeholders and Data Stewards to identify and unlock opportunities and data quality issues identify relevant data sets needed for data analytics.
  • Identify areas for data quality improvements and help to resolve data quality problems through the appropriate choice of error detection and correction, process control and improvement, or process design strategies.
  • Maintain effective working relationships in order to coordinate, integrate, and defend customer requirements with technical assessments forecasts, system capabilities, and plans.
  • Ensure you anticipate; understand the upstream and downstream data impact and directs the development, implementation, and management of control structures and business rules used to govern data transformations.
  • Supervise: effectively communicate with enterprise Data Stewards, data specialists, and IT system support teams to resolve data management conflicts and escalate issues to management on a timely basis.
  • Facilitate timely and quality release of data and analytic products to external partners for appropriate purposes, without compromising privacy and confidentiality concerns.
  • Coordinate with the database administration group to ensure day to day activities (statistics collection and reporting) are performing in the most efficient manner (data warehouse and big data environments).
  • Govern: conduct research on emerging data integration products, languages, and standards in support of procurement, development, security, and integration efforts in relation to the cloud, BI, and big data management.
  • Maintain and advise relevant stakeholders on data governance related matters in a specific domain (Customer, Material, Vendor, Finance, Consumer) with a focus on the business use of the data.
  • Systematize: data call for changes to production systems, determines impact on existing systems, processes and develops appropriate specifications, enhancements and or procedures to comply.
  • Create reporting and/or data quality scorecards to enable collaboration with business data owners and stakeholders to provide visibility and drive decisions for ensuring data consistency and quality.
  • Advise on various projects and initiatives to ensure that any data related changes and dependencies are identified, communicated and managed to ensure adherence with the Enterprise Data Governance established standards.
  • Manage the customer data governance framework that establishes the mechanisms through which people, process, and technology elements are synthesized to effectively manage customer data.
  • Assure your organization complies; ls and cos vision is to be a data driven organization that applies analytics, machine learning, and automaton to making decisions, and predicting and shaping desired outcomes across the business.
  • Make sure that your organization complies; across multiple systems, for a variety of investment products, with the goal of providing accurate, timely data that is used for analytics, risk management, trading, finance, compliance, marketing and client reporting.
  • Represent technology in the data governance organization and provide progress reports to board management and oversee periodic updates to data governance technology roadmap.

 

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