Data governance outlines the roles and allocates decision-making responsibilities to these people. It establishes enterprise-level standard and guidelines. It even ensures compliance with data laws and corporate strategies. With clear responsibilities the implementation of projects depending on data is quick and the data quality obtained is valuable to make core business decisions for growth and success.
Setting a data governance framework is a huge challenge. Business owners can approach EWSolutions for a data governance training course. They will learn to follow the following steps –
- Define the deliverables like data management roadmap, strategy, governance framework, architecture, model, and lifecycles.
- Identify needed activities in the process map that includes operational, tactical, and strategic. Process map activities must be allocated to employees within your company.
- Define the roles while allocating the activities to your employees.
- Determine the number of people needed for implementing the data governance process.
- Set mandate [authority] and decision rights.
- Define implementation plan.
- Select the correct employees.
Data governance design’s basic principles are –
- Enterprise-level data governance needs collaboration between top-level management to IT to the non-tech workforce. It means you can assign roles and responsibilities to employees working in different departments.
- Data management roles highlight the data provision for different business needs. The analytic roles deliver diagnostic reports across the enterprise. Both roles depend on one another and allow data supply chains.
The customary data governance roles are –
- Data stewards – Their role is to evaluate the data needs and issues as well as support project implementation and digitalization initiatives for their specific domain. Their roles can be divided into business data stewards and technical data stewards. The former is liable for defining data in specific responsible areas, while the latter designs, creates, sets up, and manages intangible and logical data models.
- Data owners – The senior managers are assigned this title. Their role is split into – data content owner and data definition owner.
- Data editors – They operate data life-cycle according to defined standards.
- Executive sponsors – They offer strategic direction, sponsorship, funding, and supervision for the data management process.
- Chief data officer – Their role is to support the data management board to set a data governance framework and define a solid strategy. They are also responsible for data stewardship management daily.
- Data quality manager – Defines how to maintain data quality using specific metrics and methodologies.
- Data expert – Their role is to communicate and give training to data editors about data definition.
The assignment of data governance roles depends on multiple variables like the company’s maturity and data management mandate. Nevertheless, three groups need to work together including –
- Data management teams [data steward, data quality managers, data documentation managers, and data architects]
- IT department
- Business units/support functions [data definition owner, data content owner, data experts, and data editors]
As analytics are gaining more importance in the majority of data-driven organizations, the roles of data management need to be connected with data analysts and data scientists.
Data management principles even help organizations to communicate abstract data management topics tangibly. For example, everyone is liable for data quality – here data quality becomes everyone’s responsibility and not only for the central data management group. It explains why data matters and why each one is responsible.
