Data and information management
The smooth operation of an organization is shaped by the ability to answer six questions with the information it manages: who, what, where, when, how and why.
Without effective information management and, more broadly, knowledge management, the organization’s ability to answer these questions becomes significantly more difficult, which begins to take resources away from focusing on the actual business.
In information management (and data management), information processes are organized in such a way that the availability, discoverability and usability of data and information can be ensured throughout the entire lifecycle of data. Information management usually encompasses aspects of information security, data protection and data quality as well. In addition to best practices, there are numerous domestic and EU regulations concerning information management (such as the Information Management Act or the Data Governance Act).
Defining, finding and effectively utilizing information is often seen as challenging. To gain maximum benefits and information from data, it should be acquired, grown, developed, planned and utilized effectively. This, in turn, is not possible unless the organization builds physical and social structures that guarantee comprehensive utilization of information.
An organization should have the ability to maintain, develop, coordinate, utilize and further refine its information. Knowledge management refers more broadly to the systematic management of information and expertise in an organization. It helps an organization anticipate, implement, adapt, evaluate, and develop its operations – often making them more efficient.
Knowledge management capabilities are built on a foundation of information infrastructure, technologies as well as organizational structures and organisational culture.
We help our clients answer questions on information management and knowledge management by producing high-quality logical, conceptual, process and data models, and by harmonizing the client’s data to match these models. We identify and resolve any potential overlaps, conflicts and gaps in the data.
We also help our customers in adopting best industry practices for managing and developing operations, roles and data as an entity, without forgetting semantic interoperability. We commonly use methods such as Data Vault 2.0, MDM (master data management), and GDBMS.