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Data Governance & Compliance
Decide to implement Data Governance & Compliance to run your company comprehensively. Be confident your data is consistent and reliable. Data Governance & Compliance are systems for businesses to comprehensively manage data and related processes and resources, both personal and technological. Data Governance & Compliance covers data creation, processing and use. Data management takes place throughout the organization, which is why it is so important for IT to work with the business to improve data quality and reliability. These activities support key business initiatives in the organization including adapting to current changes in the law such as RODO and GDPR.
What you will gain after
implementing Data Governance & Compliance
Data Governance & Compliance is more than an isolated one-off project, it is an ongoing process, this is why it is so important to be arm-to-arm with a reliable partner here.
Democratization of data
Share more data by empowering your business with a data-sharing marketplace for employees. Data democratization makes data accessible to both technical and business users. Save time and make optimal decisions for your business with new data use and data transfer.
Securely manage personal data
Digital transformation in your high responsibility for data security. Ensure the security of personal data and make it easy to detect, use and control.
Compliance with legal regulations
Comply with regulations and implement privacy laws by centrally managing people's privacy preferences. Manage people's data you own transparently in a single view of rights and consents.
Best practices related to Data Governance & Compliance
Data Governance & Compliance is not a single project, but ongoing evolving management of data, processes, and technologies.
That’s why we always follow the best practices during implementation, driven by:
- define roles and responsibilities in the organization,
- defining the architecture and solutions used,
- locating critical data that impacts business objectives,
- introducing data quality metrics,
- establish measurable objectives,
- standardize data definitions,
- defining KPIs for users authorized to generate data,
- build awareness and optimize communication within the organization,
- identify a network of data business owners, i.e., key people working with the data,
- tailoring the implementation to the organization in question,
- defining data domains.
