Data Governance Practice
Data Governance Practice | Overview
Data Governance focuses on improving data quality, protecting access to data, establishing business definitions, maintaining metadata and documenting data policies. Effective data governance serves an important function within the university, setting the parameters for data management and usage, creating processes for resolving data issues and enabling data users to make decisions based on high-quality data and well-managed information assets. This is done by setting up a system of decision rights and accountabilities for data-related processes, executed according to agreed upon models.
Data Governance Best Practices provide the basis for standing up a formal data governance practice. Best practices can be thought of as the required behaviour for aninstitutiontoachieve and maintain common "ways of doing things"around the governance of data.
About the Practice
To undertake a leadership role in the creation, implementation and oversight of the enterprise-wide information and data management goals, standards, practices and processes aligned with the goals of the institution.
To provide expert advice and support in relation to all aspects of information and data governance including data trusteeship, data protection, data privacy, and information usage, classification and retention.
To promote data governance at an executive and senior management level.
To build a data governance framework that establishes consistent definition and understanding of data, establishes ownership of data, establishes how metadata is managed and establishes organizational roles and responsibilities.
Enable the university community to treat information as an institutional asset that can be used and shared with confidence to support evidence-based decision-making and take informed action.
Purpose
The purpose of IDG at UCalgary is to … “Use Strategic Data with Confidence”.
Strategic data is the data that enables informed decision-making, while confidence in that data equates to validating and trusting that the data is accessible and timely, complete and accurate, understood and secured.
Scope
The scope of data governance is the management of structured institutional data, and decisions regarding the collection, retention, duplication, quality control, definition and sharing of such data. At this time only Business Information Assets is being considered. Scholarly Information Assets, and, Health Information Assets are excluded. (Please see Information Asset Management Policy for definitionsof these terms.)Records management and unstructured data are also currently notwithin the scope of the Institutional Data Governance Practice framework.
The primary drivers for implementing data governance and this framework at the ɫ are as follows:
- improving data quality and thereby improving confidence in institutional data;
- facilitating and enabling auditable/certified reporting sources that will allow consumption of data from authoritative data assets that are certified for authenticity;
- identifying information stewardship. Better accountability and information stewarding will improve trust and confidence in data being reported both externally and internally;
- establishing agreed upon and enforceable Institutional agreements for data sharing and use;
- establishing consistency in understanding of data definition. A better understanding of data definitions will promote consistent usage; and,
- producing effective data governance processes, standards, procedures, and guidelines.
The following principles are set forth as minimum standards to govern the appropriate use and management of institutional data:
- institutional data is the property of the ɫ and shall be managed as a key asset;
- unnecessary duplication of institutional data is discouraged;
- quality standards for institutional data shall be defined and monitored;
- institutional data shall be protected;
- institutional data shall be accessible according to defined needs and roles;
- institutional metadata shall be recorded, managed and utilized;
- institutional representatives will be held accountable to their roles and responsibilities;
- necessary maintenance of institutional data shall be defined;
- resolution of issues related to institutional data shall follow consistent processes; and
- Information Stewards are responsible for the subset of data in their charge.
Our Approach
Non-Invasive Data Governance Approach is the practice of applying formal accountability and behaviour through non-threatening roles and responsibilities to existing and/or new processes to assure that the definition, production and usage of data assures regulatory compliance, security, privacy, protection and quality.The term non-invasive describes how governance is applied to assure non-threatening management of valuable data assets. The goal is to be Transparent, Supportive and Collaborative whenever possible.
The ɫ’s Institutional Data Governance Practice follows the Non-Invasive Data Governance approach developed by Robert K. Seiner (KIK Consulting & Educational Services). Bob Seiner is widely recognized for his expertise in, and knowledge of, the field of data governance.
Some key characteristics of a non-invasive data governance approach:
- Development of an operating model that is aligned with current job activities and practices of subject matter experts in the institution. This alignment provides formal recognition of particular individuals as Information Stewards and subject matter experts. As well, this alignment allows for a “seamless” transition to adopting Information Stewardship roles and responsibilities.
- Formalization of decision escalation processes and collaborative decision-making. This formalization provides the needed authoritative voice to Information Stewards and subject matter expertsso that they can effectively govern critical data. As well, this formalization guides data users in requesting access to data.
- Leveraging the existing practices, methodologies and processes that are already working successfully in the institution. This information is formally documented, along with critical data element metadata, and shared across the institution from a central repository.
- Transparency is important in the practice of non-invasive data governance in order to maintain trust and confidence in how data is shared across business units, as well as how data is used/reported by individuals. Communication across the institution at all levels of data governance, identification of Information Stewards and subject matter experts, and, access to information (such as roles and responsibilities, processes, and critical data element metadata) all work together to ensure the practiceis inclusive and enables everyone to use strategic data with confidence.
The ɫ embarked on this initiative in order to develop and implement an Institutional Data Governance Practice to improve the institution’s confidence in the usage of strategic data. The overall goal of the practice is to leverage data as a strategic asset that enhances the university’s decision-making capabilities by enabling and supporting improvements in the delivery of trusted and accessible data.