Berlin, February 4, 2020 | Data Governance is not a project but a philosophy. It demands the setup of rules and policies regarding all company data and compliance by any data user. Data governance lays the foundation for digital sustainability and fuels the company profit as well as cost efficiency. This blog post explains the importance, relevance and possibilities of data governance.
What is data governance?
Data governance is the framework for data quality management (DQM) and defines which roles take over the tasks of DQM with which responsibilities. General and specific standards for the handling of data and its management in companies can be defined in the form of a data governance guidelines, which should be considered by all employees.
Data governance as a framework for DQM contains three basic design elements:
- Definition of necessary tasks within the DQM (e.g. the development of a data quality strategy and the definition of data maintenance processes)
- Identification of roles (responsibilities which have to be taken on by employees) in the fulfillment of these tasks (these include, for example, the data stewards who implement data quality standards)
- Determining the responsibilities of the individual roles when performing the DQM tasks
Hence, data governance defines the scope of all DQM actions while cutting itself off the operational implementation of DQM activities.
Relevance of data governance
High-quality data is the company’s basic prerequisite for meeting customer requirements: In an era of advanced digitalization and increasingly individual customer requirements, companies must often adapt their business processes. With the help of data governance the foundations for improving and securing data quality in companies are laid – which means that data can be used more efficiently in the medium term.
Examples that illustrate the relevance of high-quality data
- Customer management: All customer data must be available for high customer satisfaction and good customer service. This often requires the excerpt of data from various information systems (e.g. CRM and data warehouses). Customer data integration can only be successful if the data quality is equally high in all systems.
- Corporate management: For important decisions in a company relevant information must always be consistently and reliably available. Poor data quality means that factors become incorrect and wrong decisions are made. To avoid this, companies need a DQM that goes beyond the limits of a system.
- Official and legal requirements: More and more requirements and guidelines must be observed by companies. In order to be able to meet the associated burden of proof, companies have to be able to provide the necessary data.
A company-wide high data quality is therefore crucial for the effective fulfillment of the company goals. In other words, poor data quality causes costs and slows down corporate success.
Data governance opportunities
For the introduction of data governance and corresponding guidelines it is necessary to determine the current state of the DQM activities. Depending on the status quo an investment in the IT area can make sense in the next step to enable the new tasks to be fulfilled. The initiators must simultaneously seek support for the idea of data governance among colleagues, other departments, the management and the IT department.
During the introductory phase basic data deficiencies are initially determined by the respective specialty departments. In addition, all company data is simultaneously checked by data profiling which means by evaluating the data quality of data records. This can for instance be realized with the help of data quality software.
Subsequently, a company-wide systematic procedure for the management of digital data is necessary for permanent assurance of high data quality even when new data is created. This is based on the data governance guidelines and is implemented by the data stewards of the individual departments.
Summary
Data governance is the framework for activities related to data quality management. It uses guidelines to determine which standards are used in the company and which areas of responsibility should handle the tasks to achieve high data quality. High data quality is so important for companies because today’s digital and market requirements cannot be met without data. Ultimately, data governance leads to more business profits and lower costs.
