To be data driven, an organisation should manage its data with metadata, and that metadata itself should in turn be managed. Regardless of types and uses of metadata, metadata management decisions should be driven by business requirements. All agencies will have different business drivers for managing metadata, which may vary across the organisation and across data repositories. Some common business drivers for implementing a consistent and structured approach to metadata management may include:
Understanding and describing existing data holdings
As well as providing a rich source of information about the context, history and origin of a data asset, metadata can also be used as a tool to help identify, locate and catalogue existing agency data holdings. Metadata is also useful in helping people from different parts of the organisation to identify differences and similarities between data assets. Understanding what data your agency holds is crucial to being able to use it efficiently and is also the first step to implementing an effective data governance strategy.
Facilitating data use and re-use
In order to use data appropriately and effectively, it must first be understood. Because metadata should accurately and consistently represent the content of data, it provides users with a level of confidence and understanding regarding both what the data is, and what it can be used for. Metadata can also help identify and enable multiple uses for the same data, such as strategic information within an agency, or information sharing between agencies.
Effective data governance
Data governance is concerned with maximising the value of data by exercising authority and control over data management practices. Effective data governance is underpinned by a consistent approach to metadata which promotes efficiency as well as knowledge of where data is located, what it means and what protections it requires. Metadata plays a critical role in relation to data governance, because it is the key to describing an organisations data and business processes, as well as their relationship to each other.
Increased confidence in data quality
Data quality is highly dependent on data governance, which in turn depends on effective metadata management. Because metadata describes data elements in terms of a controlled vocabulary (or data dictionary), it provides structure and consistency to those creating metadata as well as confidence to consumers regarding how the data can be used and whether it is fit for the intended purpose.
Metadata management can aid discoverability of data both within and between agencies by ensuring that it is described accurately, consistently and completely.This allows potential users, whether internal to the agency, external to the agency or a member of the community to discover, understand and request access to the data they require. If compiled into a data catalogue at the dataset level, metadata can act in a similar way to a library catalogue, allowing potential users to understand all relevant information (update frequency, security classification, licensing conditions etc) required to access and use the desired information.
Supporting data analytics
Precise data analytics relies on data which is both accurate and appropriate for the task at hand. Reliable and complete metadata, including consistent definitions of data elements, provides a level of confidence to those undertaking data analytics activities that the data they are analysing is fit for the intended purpose. Metadata provides a level of assurance to data analysts that the data they are using is not incorrect, out of date or unreliable.
Reliable and well managed metadata can help to ensure regulatory compliance in relation to agency specific legislation as well as the Information Privacy and the Right to Information Acts. Metadata can help to ensure that private data is adequately protected, and that information requested through the RTI process can be readily located within the designated timeframes. Effective metadata management can also assist agencies to meet the requirements of a range of other QGEA policies such as Information access and use (IS33), Information security policy (IS18:2018), the Queensland Government Information Security Classification Framework (QGISCF) and the Records governance policy.
Improving operational efficiency
Ensuring the effective management of metadata has the potential to produce a range of operational efficiencies such as streamlined workflows and improved communication particularly between data consumers and IT professionals. In addition, metadata management may facilitate the identification of redundant data and processes, reduce the amount of money spent on data storage and support better data driven decision making within agency business units.