A 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)
- 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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