What is a Chief Data Officer (CDO)?

chief data officerA Chief Data Officer (CDO) helps bridge the gap between technology and business. This person evangelizes an enterprise-wide Data Management strategy at a senior level. The CDO leads Data Management initiatives, enabling an organization to leverage its data assets and gain a competitive advantage from them. A CDO tends to be part business strategist, adviser, Data Quality Steward and all-around Data Management ambassador.

While the specific requirements and functions of a CDO are specific to each company, common responsibilities include:

  • Establish an organizational Data Strategy.
  • Align data-centric requirements with available IT and business resources.
  • Establish Data Governance standards, policies and procedures.
  • Provide advice (and perhaps services) to the business for data-dependent initiatives, such as business analytics, Big Data, Data Quality and data technologies.
  • Evangelize the importance of good Information Management principles to internal and external business stakeholders.
  • Oversee data usage in Analytics and Business Intelligence.

Other Definitions of a Chief Data Officer Include:

  • “A linchpin of digital business transformation.” (Gartner)
  • “Person responsible for: (Jennifer Zaino, DATAVERSITY®)
    • Data Analytics initiatives
    • Data Governance initiatives
    • Defining the Analytics Strategy for the organization
    • Ensuring that information is reliable and valuable.”
  • “Help bridge the gap between technology and business and evangelize an enterprise-wide Data Management strategy at a senior level.” (Steve Stine)
  • A “bridge between functional leaders who need information in real time and the IT department.” (Forbes)
  • Manager, “of torrents of data, critical to a company’s success.” (Harvard Business Review)
  • The “central player in the business of data, including security.” (MITCDOIQ Symposium)

Businesses Need a CDO to:

  • Help with decision making through data.
  • Find patterns and connections within data.
  • Provide data value to investors and customers.
  • Provide a thorough understanding all the platform connections needed.
  • Abstract complex connections between data.
  • Communicate with different departments and building relationships with them around data needs.

 

 

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