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What is a Chief Data Officer (CDO)?

By   /  January 15, 2018  /  No Comments

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.



Photo Credit: Profit_Image/Shutterstock.com

About the author

Michelle Knight enjoys putting her information specialist background to use by writing technical articles on enhancing Data Quality, lending to useful information. Michelle has written articles on W3C validator for SiteProNews, SEO competitive analysis for the SLA (Special Libraries Association), Search Engine alternatives to Google, for the Business Information Alert, and Introductions on the Semantic Web, HTML 5, and Agile, Seabourne INC LLC, through AboutUs.com. She has worked as a software tester, a researcher, and a librarian. She has over five years of experience, contracting as a quality assurance engineer at a variety of organizations including Intel, Cigna, and Umpqua Bank. During that time Michelle used HTML, XML, and SQL to verify software behavior through databases Michelle graduated, from Simmons College, with a Masters in Library and Information with an Outstanding Information Science Student Award from the ASIST (The American Society for Information Science and Technology) and has a Bachelor of Arts in Psychology from Smith College. Michelle has a talent for digging into data, a natural eye for detail, and an abounding curiosity about finding and using data effectively.

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