ICT information and knowledge manager jobs in Finland
ICT information and knowledge managers contribute to the definition of organisational information strategy and apply information and knowledge creation, editing, storage, and distribution policies. They manage the maintenance and evolution of structured and unstructured information. They create digital structures to enable exploitation and optimisation of information and knowledge, manage data analysis and enable business intelligence.
ICT information and knowledge manager - Which skills are essential?
Apply migration and conversion methods for existing data, in order to transfer or convert data between formats, storage or computer systems.
The type of infrastructure which defines the format of data: semi-structured, unstructured and structured.
The plan defined by a company which sets the information security objectives and measures to mitigate risks, define control objectives, establish metrics and benchmarks while complying with legal, internal and contractual requirements.
The tools used to transform large amounts of raw data into relevant and helpful business information.
The methods through which information is generated, structured, stored, maintained, linked, exchanged and used.
Analyse data gathered from sources such as market data, scientific papers, customer requirements and questionnaires which are current and up-to-date in order to assess development and innovation in areas of expertise.
The methods of artificial intelligence, machine learning, statistics and databases used to extract content from a dataset.
The ICT systems that can be used to support business or organisational decision making.
Set up structures and distribution policies to enable or improve information exploitation using appropriate tools to extract, create and expand business mastery.
Communicate with clients or users in order to identify which information they require and the methods with which they can access it.
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.
The techniques and methods used for eliciting and extracting information from unstructured or semi-structured digital documents and sources.
The process of classifying the information into categories and showing relationships between the data for some clearly defined purposes.
Study the external and internal environment of an organisation by identifying its strengths and weaknesses in order to provide a base for company strategies and further planning.
Processes which an organisation applies to improve efficiency, set new objectives and reach goals in a profitable and timely manner.
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.
Develop and manage methods and strategies used to maximise data quality and statistical efficiency in the collection of data, in order to ensure the gathered data are optimised for further processing.
The online tools which analyse, aggregate and present multi-dimensional data enabling users to interactively and selectively extract and view data from specific points of view.
Create visual representations of data such as charts or diagrams for easier understanding.
The information that is not arranged in a pre-defined manner or does not have a pre-defined data model and is difficult to understand and find patterns in without using techniques such as data mining.
Organise information using systematic methods such as mental models and according to given standards in order to facilitate user information processing and understanding with respect to the specific requirements and characteristics of the output media.
Identify relevant internal and external information sources and providers. Organise the information workflow and define information deliverables.
Use specific techniques and methodologies to analyse the data requirements of an organisation's business processes in order to create models for these data, such as conceptual, logical and physical models. These models have a specific structure and format.
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.
ICT information and knowledge manager - Which skills are useful but not essential?
Evaluate the implicit mastery of skilled experts in an ICT system to make it explicit for further analysis and usage.
Gather the latest information on existing information systems solutions which integrate software and hardware, as well as network components.
Explore large datasets to reveal patterns using statistics, database systems or artificial intelligence and present the information in a comprehensible way.
Design and implement business processes and technical solutions to guarantee data and information confidentiality in compliance with legal requirements, also considering public expectations and political issues of privacy.
The principles, ethical issues, regulations and protocols of data protection.
Define the architecture, composition, components, modules, interfaces and data for integrated information systems (hardware, software and network), based on system requirements and specifications.
The mechanisms and regulations which allow for selective access control and guarantee that only authorised parties (people, processes, systems and devices) have access to data, the way to comply with confidential information and the risks of non-compliance.
Communicate with users to identify their requirements and collect them. Define all relevant user requirements and document them in an understandable and logical way for further analysis and specification.
Give instructions to colleagues and other cooperating parties in order to reach the desired outcome of a technological project or achieve set goals within an organisation dealing with technology.
The process of revealing data issues using quality indicators, measures and metrics in order to plan data cleansing and data enrichment strategies according to data quality criteria.
Use the available ICT systems that can be used to support business or organisational decision making.
Apply models and tools such as online analytical processing (OLAP) and Online transaction processing (OLTP), to integrate structured or unstructured data from sources, in order to create a central depository of historical and current data.