Profession chief data officer

Chief data officers manage companies' enterprise-wide data administration and data mining functions. They ensure data are used as a strategic business asset at the executive level and implement and support a more collaborative and aligned information management infrastructure for the benefit of the organisation at large.

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Personality Type

Knowledge

  • Decision support systems

    The ICT systems that can be used to support business or organisational decision making.

  • Information structure

    The type of infrastructure which defines the format of data: semi-structured, unstructured and structured.

  • Data mining

    The methods of artificial intelligence, machine learning, statistics and databases used to extract content from a dataset.

  • Data storage

    The physical and technical concepts of how digital data storage is organised in specific schemes both locally, such as hard-drives and random-access memories (RAM) and remotely, via network, internet or cloud.

  • Business processes

    Processes which an organisation applies to improve efficiency, set new objectives and reach goals in a profitable and timely manner.

  • Visual presentation techniques

    The visual representation and interaction techniques, such as histograms, scatter plots, surface plots, tree maps and parallel coordinate plots, that can be used to present abstract numerical and non-numerical data, in order to reinforce the human understanding of this information.

Skills

  • Apply information security policies

    Implement policies, methods and regulations for data and information security in order to respect confidentiality, integrity and availability principles.

  • Manage ICT data classification

    Oversee the classification system an organisation uses to organise its data. Assign an owner to each data concept or bulk of concepts and determine the value of each item of data.

  • Manage ICT data architecture

    Oversee regulations and use ICT techniques to define the information systems architecture and to control data gathering, storing, consolidation, arrangement and usage in an organisation.

  • Define data quality criteria

    Specify the criteria by which data quality is measured for business purposes, such as inconsistencies, incompleteness, usability for purpose and accuracy.

  • Utilise decision support system

    Use the available ICT systems that can be used to support business or organisational decision making.

  • Manage data

    Administer all types of data resources through their lifecycle by performing data profiling, parsing, standardisation, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit for purpose, using specialised ICT tools to fulfil the data quality criteria.

Optional knowledge and skills

sql server data quality assessment information architecture db2 database development tools develop information security strategy ca datacom/db unstructured data mdx openedge database cloud technologies linq data models information confidentiality sparql manage business knowledge information categorisation microsoft access xquery database information extraction oracle relational database apply change management database management systems query languages report analysis results online analytical processing postgresql mysql implement ict risk management coordinate technological activities information security strategy n1ql business intelligence filemaker (database management systems) integrate ict data teradata database resource description framework query language ibm informix deliver visual presentation of data ldap objectstore