Profession data entry clerk

Data entry clerks enter coded, statistical, financial and other numerical data into electronic equipment, computerised databases, spreadsheets or other data repositories using a keyboard, mouse, or optical scanner, speech recognition software or other data entry tools. They enter data into mechanical and electronic devices to perform mathematical calculations.

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Personality Type

  • Conventional / Realistic

Related professions typist

  • Typist or word processing operator

Knowledge

  • Query languages

    The field of standardised computer languages for retrieval of information from a database and of documents containing the needed information.

  • Documentation types

    The characteristics of internal and external documentation types aligned with the product life cycle and their specific content types.

  • Resource description framework query language

    The query languages such as SPARQL which are used to retrieve and manipulate data stored in Resource Description Framework format (RDF).

  • Database

    The classification of databases, their purpose, terminology, characteristics, models and use such as document-oriented databases, XML databases and full text databases.

Skills

  • Perform data cleansing

    Detect and correct corrupt records from data sets, ensure that the data become and remain structured according to guidelines.

  • Apply information security policies

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

  • Maintain data entry requirements

    Uphold conditions for data entry. Follow procedures and apply data program techniques.

  • Apply statistical analysis techniques

    Use models (descriptive or inferential statistics) and techniques (data mining or machine learning) for statistical analysis and ICT tools to analyse data, uncover correlations and forecast trends.

  • Process data

    Enter information into a data storage and data retrieval system via processes such as scanning, manual keying or electronic data transfer in order to process large amounts of data.

Optional knowledge and skills

ldap manage ict data classification mdx n1ql establish data processes implement data warehousing techniques implement data quality processes apply organisational techniques normalise data abbyy finereader sparql data models manage data collection systems data storage linq omnipage xquery manage data optical character recognition software information confidentiality