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The concept of data management at every stage of their presence in the company, from the acquisition process, through processing, identification of data flow, to properly ensuring their security and privacy. Data Governance is aimed at exercising continuous control of key data, incl. in terms of their quality, suitability for business activities and storage security.
Constantly growing data resources are a serious challenge for any company that consciously uses them in everyday management. Effective data control becomes a fundamental necessity, not only in order to build a competitive advantage, but also to minimise risks, and meet the requirements of an increasingly regulated world before problems begin (wrong decisions, unjustified expenses, GDPR penalties, risks resulting from AML, restrictions of the Polish Financial Supervision Authority, etc.).
Rules and regulations
Formal regulations introducing the rules of information management by individual Organisational Units (e.g. Data Management Policy, Data Quality Policy).
Information Model
The division of information resources into individual Business Data Areas and Sub-areas and the assignment of data ownership.
Roles and Responsibilities
Detailed definition of the roles and responsibilities of individuals and Organisational Units in the data management process.
Data management processes
Structure of the main processes, definition of operational methods of data management and implementation of appropriate tools supporting the main processes.
A specialised tool for monitoring and analysing data quality in the area of important business processes of the company, such as: verification of correctness, completeness, consistency and adequacy of data.
biDQM provides automated mechanisms for controlling and assessing data quality in an organisation.
It also allows you to collect and present the results of analyses in the form of dedicated reports.
Systematized and repeatable data quality monitoring processes..
Automation in the field of commissioning, alerting and reporting on data verification processes.
Monitoring the status of data processing processes allows for quick detection of irregularities.
IT solution for consolidation, synchronization and unification of master data processed in various organisational systems.
Advanced algorithms for connecting and improving data quality automate the process of their integration.
The result is a centralised repository that is a reliable source of information necessary for effective business operations.
Ensuring a consolidated source of key master data.
Improving the visibility and control of business activities.
Enrichment and automated synchronization of master data based on internal resources and external registers.
Intelligent tools for discovering, profiling and detecting the informative content of text data/metadata, e.g. identification of personal data in accordance with the requirements of the GDPR.
The solution extracts essential customer information from unstructured texts and uses it for personalised marketing, content categorisation, mood analysis, loyalty analysis, customer feedback, fraud detection and risk analysis.
A complete and up-to-date picture of data quality.
Easy-to-use interface for business users.
Possibility to use the data directory for subsequent projects.
A metadata management module that automatically saves and stores data about the company's information resources.
It allows you to categorize and catalog data according to a specific model, both on the technical and business level.
Stores definitions and associations of all data, as well as allows you to assign ownership of data and business concepts.
Ability to share information from the data catalogue across the organisation.
Categorisation of data in terms of their criticality and regulatory requirements, e.g. personal data (GDPR).
Effective management of information resources to improve business processes, build new applications and reports.
Ability to identify data from many different sources
