The dictionary meaning of the word Governance is “The action or manner of governing a state, organisation, etc”.
And simply because every organisation wants to be uniquely different, data governance can be different things to different organisation here. So most organisations will have their own distinct official definition of data governance and freedom to choose the knowledge areas from any framework or model in their implementation.
The best definition found online is — “Data Governance refers to the organisational bodies, rules, decision rights, and accountability of people and information systems as they perform information related processes to ensure the effective and efficient use of information in enabling an organisation to achieve its goals”
Underneath organisation-specific-definitions of data governance lie some common themes in the areas of security, availability, storage, effective use, and the management of data.
How —
Data governance differs from data management -
Data governance = Decision, rules, rights, regulations and policy making for the organisation.
Data management = Execution of all of the governance policies, it is an operational function of an organisation.
What —
Data Governance is not —
Data Governance is not a technology function. It is a business function and forms a bridge between business and technology.
Data Governance is a process and not a project. It is a screaming voice of the data. (Because data speaks 😝, do you remember?).
Who -
The data governance organisation/office structure should be made up of –
- A cross-functional executive steering committee of executive leaders.
- A Data Governance Board comprising of data stakeholders that assists to define, plan and execute.
- Data Stewards kind of new roles responsible for the day-to-day work .
Data Governance Council/Office — This is a centralised, cross-functional decision-making authority and their responsibilities include but not limited to -
- Direct and strategically align data governance programmes to enterprise vision.
- Act as a central hub for key data assets and components, such as policies, processes, data standards and compliance.
- Influence, help and enable organisational strategy for better analytics and decision-making around data.
When -
- Organisations must assess themselves for market position or performance more frequently. with global competition getting fierce, the current market conditions do not allow for inefficiencies historically tolerated.
- increased focus on data quality and control procedures for data consistency, accuracy.
- Need for operational excellence and measurement by clearly defined roles and responsibilities.
- Mandatory regulation and compliance requirements call for formal data governance.
Finally, some must-have elements that should feature in data governance plan document -
- Accessibility — Are data available to right people at right time.in right format.
- Security — Clear guidance on rules and definitions for authorised and non-authorised users of data.
- Consistent — Single version vs multiple versions of truth.
- Quality — Conformance to agreed data quality, accuracy and standards.
