Compliance & Audit

Data Quality Assessment & Frameworks

Blindata is your solution for data quality and audit processes. It enables you to collaborate across business functions, comply with regulations, assess risks and improve performance. With Blindata, you can create a data quality framework that suits your company’s needs and goals.


Data driven companies are often equipped with an audit function, not only in regulated sectors. A data quality framework can increase trust in the audit process, using data to verify compliance, assess risks and identify areas for improvement. This requires collaboration between different business functions and continuous training of staff. Blindata offers a flexible and collaborative framework that can help your company to design data quality processes.


Blindata helps organizations to meet the data quality requirements of various data privacy regulations, such as GDPR, as well as industry specific laws, like Solvency II, PCI DSS and HIPAA. Common data quality needs of these regulations are:

  • Accuracy: The data should be correct and free of errors. For example, GDPR requires that personal data be accurate and kept up to date.
  • Completeness: The data should be sufficient and not missing any relevant information. For example, Solvency II requires that data be complete and reliable for the calculation of technical provisions.
  • Appropriateness: The data should be suitable and relevant for the intended purpose. For example, HIPAA requires that data be appropriate for health care operations.

Data Governance tools can help to become accountable for the use of your data: with Blindata you can create a data quality framework that suits your company’s needs and goals.

Data Asset Inventory

Identify every element in your data landscape, at column level.

Understand Data Impact

Trace data transformations and what happens if you need to change something.

Define And Evaluate Risks

Lists the types of risk and how frequency and severity impact the level of risk.

Minimize data risk

Implement quality controls based on priorities, to optimize the efforts.

How To

Mapping data assets is crucial to auditors as it enhances their skills and knowledge on data and analytics, as well as collaborating with other data users. Blindata Data Catalog provides a comprehensive view of an organization’s data assets, including their structure, relationships, and dependencies, making it easier to identify what data needs to be protected. Blindata Agent automatically collects metadata, connecting to both on-premise systems and cloud services, potentially identifying the type of protection applied to catalog items.

Auditors aren’t typical data professionals, their knowledge is more close to business functions than IT people. This is where Blindata Business Glossary comes in handy. Its multilevel hierarchical structure maps not only business terms, but also entities. You can define relationships between mastered objects and visualize them in the Knowledge Graph. To connect logical and physical models Blindata Data Classification links Business Entities and Business Terms to Physical Entities, like tables, columns, reports, views, ecc…. Using custom rules it is possible to identify PIIs and other sensitive information,
Blindata helps organizations to comply with various data privacy regulations, such as GDPR, as well as industry specific laws, like Solvency II, PCI DSS and HIPAA.

As data moves through the enterprise, from source to end users, it can influence a variety of stakeholders and processes. Having a clear understanding of the data life-cycle is crucial during the auditing process. Blindata Data Lineage gives a clear and interactive representation of data flows, while Blindata Agent can collect metadata to automatically build the flows at column level.

The data quality monitoring process cannot be left only to the technical figures involved in the design of the Data Management processes. The definition of KQIs is instead a multidisciplinary process, which must support business processes. Blindata Data Quality provides the tools for defining KQI measurement strategies and acceptance thresholds. KQIs can be associated with the physical entities, so that it is possible for all users to be aware of the quality of the different data assets. When the value of a KQI drops below a defined value, Blindata Issue Management can be configured to automatically generate an issue, which can be traced from its opening until closing.

For an auditor having a framework for identifying weaknesses is more important than the absolute level of quality. Blindata Quality Assessment is a complete framework that defines the risk profile, identifies the inherent risk of the data assets and the mitigation capacity of the quality controls. Then the Risk Matrix calculates the residual risk for Data Asset, making clear the priorities and the margins for improvement.