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Establishing the Foundations of Data Governance Using Data and Process Design Standards and Management Practices

Training Options

  •   Duration: 90 Minutes  
  • Recorded Access recorded version only for one participant; unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)
    Price: US$289.00
  • Refund Policy


Based on industry experience, a data management life cycle will be used to show the data governance requirements for each phase of the life cycle. This will include the requirements that are be met, the resources required to support the life cycle and the data governance information to be collected and analyzed for each step.

What is it and why is it needed: A working definition of data governance will be discussed. This definition will include: the corporate motivation for and purpose of data governance, its scope and characteristics, who is responsible, who are the beneficiaries, what are the benefits and what is the cost/benefit 'equation' of data governance.

What are roles of stakeholders: Data governance is a team sport. At many places in the data management life cycle, data governance principles and concepts need to be actively used. Successful data governance implementation requires an understanding of organizational and functional roles, responsibilities and accountabilities. A set of these roles will be presented and mapped to the data management life cycle. Suggested stakeholder skills, knowledge and performance indicators will be presented

How is data governance performed: Each step of a data management life cycle will be presented in detail. Each operational step in the data management life cycle (specification, design, implementation and maintenance process ) will be presented identifying data governance requirements, stakeholder roles and performance indicators. How data design standards, data management methods, procedures and metrics fit into the data governance narrative and support the organization's goals for achieving data quality and interoperability will be included. A self-assessment questionnaire will be presented to assist participants begin to identify gaps in their data governance programs and lay the foundation for a data governance road map and action plan.

Why should you attend: In many industries, there is an exponential growth in risk that goes along with the corresponding growth in business volume and complexity. The underpinnings for supporting that business growth and minimizing risk is assuring that the corporate asset called 'data' serves the business with speed, integrity and trustworthiness. Increasingly, inadequate or incorrect data design and data management practices (i.e. 'bad data') are being associated with health, safety, security, compliance and financial issues. Whatever your responsibilities may be with regard to data, it is a growing likelihood that your accountability is growing as your responsibilities increase. In addition to the business consequences of 'bad data', penalties, fines and ultimately litigation may await you and your organization.

Ironically, there is no standard definition for data governance, but in this session what is important to know about to reduce your and your organization's 'bad data' vulnerability. In this webinar, whether you are in management or technical design, the key functions, responsibilities and success factors of your role and how they apply to the data management life cycle will be presented. Through understanding each step in the data life cycle, the needed skills, methods, procedures, technology and knowledge required to implement a successful data governance program will be presented.

Areas Covered in the Session:
  • What is data governance and why is it essential
  • What are the risks concerning data trustworthiness
  • Who is accountable for data quality and interoperability
  • What are the roles and responsibilities for data design and management
  • What is the infrastructure (methods, skills and technology) needed for a successful data governance program
  • Walk through the data management life cycle from a governance perspective
  • Conducting a data governance self-assessment
  • Developing a data governance action plan

Who Will Benefit:
  • CIO
  • CDO (Chief Data Officer)
  • Governance Officer
  • Enterprise Architect
  • Data Architect
  • QA Manager
  • Information/Data Steward
  • Compliance Officer
  • Risk Manager
  • Development Manager
  • Business Analyst
  • Line of Business Director/Manager
  • Project Manager
Hamilton Hayes is and Data Scientist and Principal Architect for Sandhill Consultants Ltd. Over time, Ham has led much of the evolution data and process products supporting education courses. He has provided his extensive expertise in information, process and enterprise modeling to numerous major North American corporations and government agencies Ham’s various roles have included serving as Business Director, Engineering manager, Consultant, Educator and Mentor. His industry experience includes aerospace, semiconductor, insurance, manufacturing, IT, human resources and government. Ham has authored articles and delivered presentations to industry groups on enterprise modeling, standards and best practices and their role in improving performance. The focus of his consulting and teaching has helped enterprises and corporations bridge the space between technical modeling and business success. He is also researcher in modeling, using data and process modeling products to model non-linear social interactions.

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