Profession big data archive librarian

Big data archive librarians classify, catalogue and maintain libraries of digital media. They also evaluate and comply with metadata standards for digital content and update obsolete data and legacy systems.

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Personality Type

  • Realistic / Artistic
  • Conventional / Social
  • Artistic / Realistic

Knowledge

  • Business intelligence

    The tools used to transform large amounts of raw data into relevant and helpful business information.

  • Database development tools

    The methodologies and tools used for creating logical and physical structure of databases, such as logical data structures, diagrams, modelling methodologies and entity-relationships.

  • Database management systems

    The tools for creating, updating and managing databases, such as Oracle, MySQL and Microsoft SQL Server.

  • Database

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

  • Data extraction, transformation and loading tools

    The tools for integration of information from multiple applications, created and maintained by organisations, into one consistent and transparent data structure.

  • Data models

    The techniques and existing systems used for structuring data elements and showing relationships between them, as well as methods for interpreting the data structures and relationships.

  • Query languages

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

  • 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).

Skills

  • Comply with legal regulations

    Ensure you are properly informed of the legal regulations that govern a specific activity and adhere to its rules, policies and laws.

  • Manage database

    Apply database design schemes and models, define data dependencies, use query languages and database management systems (DBMS) to develop and manage databases.

  • Analyse big data

    Collect and evaluate numerical data in large quantities, especially for the purpose of identifying patterns between the data.

  • Manage digital archives

    Create and maintain computer archives and databases, incorporating latest developments in electronic information storage technology.

  • 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.

  • Maintain data entry requirements

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

  • Maintain database security

    Master a wide variety of information security controls in order to pursue maximal database protection.

  • Maintain database performance

    Calculate values for database parameters. Implement new releases and execute regular maintenance tasks such as establishing backup strategies and eliminating index fragmentation. Evaluate hardware products and operating systems.

  • Manage content metadata

    Apply content management methods and procedures to define and use metadata concepts, such as the data of creation, in order to describe, organise and archive content such as documents, video and audio files, applications and images.

  • Manage archive users guidelines

    Establish policy guidelines on public access to a (digital) archive and the cautious use of present materials. Communicate the guidelines to archive visitors.

  • Write database documentation

    Develop documentation containing information about the database that is relevant to end users.

  • 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

sap data services ca datacom/db oracle relational database postgresql oracle data integrator objectstore teradata database ldap oracle warehouse builder pentaho data integration migrate existing data sql server integration services design database scheme ibm informix digitise documents informatica powercenter mysql ibm infosphere information server visual presentation techniques sql server integrate ict data n1ql xquery ibm infosphere datastage mdx perform backups qlikview expressor monitor technology trends db2 develop ict workflow information structure microsoft access design database backup specifications give live presentation linq information confidentiality filemaker normalise data openedge database statistics manage data collection systems sparql data quality assessment apply information security policies