Data governance and quality

Our data governance strategy is fundamental to how we work with big data and explains how we benefit from consistent, common processes and responsibilities.

Our data governance strategy

With great power, comes great responsibility.

Here at Creditsafe, we understand that our data holds the power to transform how companies do business and minimise third-party risk. Effective governance of our data is essential to harness this power and ensure that business professionals have accurate insights to inform their decisions.

Data Governance

Our data governance framework

Our data governance is a set of well-defined practices and processes which help us to ensure the formal management of data assets within our business. It covers issues such as security and privacy, integrity, usability, integration, compliance, availability, roles and responsibilities, and the overall management of the internal and external data flows within our organisation.

Four pillars of data governance

Processes, policies, standards, and procedures.

Principles apply to all forms of data governance and planning and guide governance decisions, processes, and systems development. The principles relating to data and broader aspects of governance are maintained by our local entity data teams, with the support of our central team. They are also reviewed and approved by the Information Security Team.

  1. Data is an asset

  2. Data is accessible

  3. Common data vocabulary

  4. Data that has shared value should be shared

  5. Data should be secure whether stored, in transit, or in use

  6. Interoperability for data, applications and technology

Organisation, roles and responsibilities

Our data is locally gathered from thousands of official and trusted sources, and managed centrally by data governance managers and formal data stewards.

Our data stewards step into both a strategic role and an operational role within the business. They are responsible for the day-to-day governance of the data under their control, while also defining the processes, policies, and standards for Creditsafe Group and all its individual entities across different geographies. As the owner of one of the largest databases in the world, we employ a greater injection of data governance at a granular level by appointing data custodians who work under data stewards and manage the day-to-day maintenance and protection of data.

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Data Governance Manager

The data governance manager runs the data governance effort and is the head of the data governance program within Creditsafe. While the data governance manager has many tasks, they are mainly associated with maintaining effective data stewardship. The data governance manager sets the standards and works with the data stewards and custodians to make sure our principles and standards are being adhered to. 

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Data Stewards 

Data stewards look after the sourcing and management of the local data. Data stewards are responsible for the management of data under their oversight, under the direction of the central data team. They appoint data custodians as required to assist in the execution of the data roadmap, policy, and procedures for their area of stewardship.

Data stewardship is concerned with taking care of data assets that do not necessarily belong to the stewards themselves. Data stewards represent the concerns of others, the entire organisation, entities, or specific data categories.

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Data Custodians 

Data custodians are entity data teams and their staff who have operational level responsibility for the collection, maintenance, dissemination, and storage of data. Stewards of data may appoint custodians to assist with data administration activities. A custodian of data is given specified responsibilities and receives guidance for appropriate and secure data handling from the stewards. A custodian has the responsibility for the day-to-day maintenance and protection of data.

Laws, regulations, standards and data quality

Creditsafe holds a high ethical threshold for data collection and protection. Our data enterprise infrastructure enables us to apply the laws, regulations and all relevant best practice frameworks to their highest degree to ensure ethical data collection and processing. 

Data privacy laws, in particular, are enforced with strict data protection policies within the business as it controls how personal information is used by organisations, businesses or the government. Our process-oriented approach toward data ethics is a reflection of our promise of harnessing the power of data for good and ensuring appropriate data confidentiality, integrity, and accessibility.

Metadata content

Metadata content is instrumental in giving us the ability to continue to develop our data governance processes for tomorrow. It gives us greater transparency and visibility into our current data governance using data lineage visualisation and auditing capabilities that allow data architects and stewards to visualise the flow of data through their environment.

Our variety of technical metadata assets helps us effectively foresee possible changes to data definitions, rules, or schemas, or analyse the root cause in capabilities when investigating or responding to data quality or security failures.

Big data needs a variety of metadata assets and Creditsafe’s ability for greater complexity of metadata collection, cataloguing, and discovery processes is a significant step toward its future readiness in data governance and protection. 


Metadata Content

Our data governance glossary

Data Profiling

Data profiling defines a set of processes for new and exisiting suppliers at Creditsafe. When identifying new potential data sources for inclusion in a new or existing Creditsafe product, we assess the data file as part of a defined purchase process. Each new supplier file must be assessed on several different criteria before approval.

Quality Assurance Checks

These are some of the minimum standards regarding the processes that we employ to manage our data sources accordingly. These include everything from supplier management, automation of file loading, standardised loading patterns and source file management, to customer query management and much more.

Change Management

At Creditsafe, modifications to the approach, reference data values and the structure/use of master data, metadata, and models used for data governance are change-managed through the Group Data Department.

Technology for Data

At Creditsafe, the Group Data Department specifies and prioritises the requirements and strategy for data management. The technology to implement those requirements and strategy are specified and implemented by IT as part of the IT roadmap for projects and improvements.

Data Quality

Creditsafe has the capability to monitor and measure the quality of data as it is captured and transformed by our processes. This is supported by automated toolsets where appropriate.

Personal Responsibility

All users of data have the responsibility of preserving the security and integrity of our data. Proper stewardship and custodianship of Creditsafe data facilitate the appropriate access to data. All data users are required to adhere to Creditsafe's personal responsibility guidelines on confidentiality, ethics, policy adherence, quality control and responsible access.

Data Strategy

As a part of Creditsafe's data strategy, a vision statement and plan for data strategy are always maintained. This sets priority and direction for data and data-related activities. Our data strategy helps us consider our overall approach for the deployment and development of its key resources: people, process, technology, and data.

Data Classification

This means that the Group Data Department ensures that there is an approved data classification classifying each data element according to an agreed definition; an example of this definition might be Sensitive (high risk), Restricted (medium risk) and Public (low risk).

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