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Management Briefing - Data governance and management at UNB

Author: ITS

Posted on Mar 9, 2016

Category: Management Briefings

Data and data governance and management sound like very dry subjects to most people, so why are they important to UNB? Let’s start with what appears to be a simple question that someone might ask that, at the core, requires “data”. How many Fredericton undergraduate students were there in the 2015 winter term? Depending on your definition of student (or data need, business purpose, or academic perspective), there were as few as 5833, or as many as 7768 undergraduate students in Fredericton last winter– nearly a 2000 student difference! Administrative and academic staff run into problems like this all the time. In general, they are left to their own devices to pick the definition that works for them, and the task at hand (whether a report, a presentation, or whatever), and explain the data as required. There is no common definition, nor even a common frame of reference for articulating one. Who gets to define ‘student’? Who says so? What if your definition doesn’t work for my needs? The Data Framework The best practice method for managing an institution’s data assets is via a data governance and management framework. Data data governancegovernance (DG) is the strategy and program that provides oversight and guidance through policies, standards and practices relating to management of the data at UNB. Data management (DM) enables DG to be made real in daily activities in the shaping of policies, practices, and guidelines within administrative authority areas including activities around the structure and design, storage, movement, security and quality of data. Technology supports DG and DM by providing tools, infrastructure, and a single, reliable enterprise-view of data. Four main focus areas – Quality & Consistency, Policies & Standards, Security & Privacy, and Retention & Archiving – guide the activities within data governance and data management and encompass all aspects of the lifecycle of data. In the course of its life, data may be extracted, exported, imported, migrated, validated, edited, updated, cleansed, transformed, converted, integrated, segregated, aggregated, referenced, reviewed, reported, analyzed, mined, backed up, recovered, retrieved & archived before eventually being deleted. Data governance and management are the collaborative processes that ensure important enterprise data assets are properly managed throughout the data lifecycle. An enterprise asset is an asset that helps achieve the goals of the enterprise and therefore need to be thoughtfully managed. Data is one of these important enterprise assets since no enterprise can be successful without high quality data. Data Governance Committee Data governance encompasses the people, processes and the technology required to create a consistent approach for handling UNB’s data. One role of DG is to improve efficiency of the enterprise by preventing so called “localized thinking” wherein users focus on resolving immediate issues faced by a unit and do not take into account the global impact of their technical and/or business decisions. The bulk of work of data governance takes place where business & technology concerns overlap, in a collaborative process designed to ensure data is well managed and maintained throughout the enterprise. To implement the framework, a broad perspective is needed. The data governance committee is a cross-functional group made up of data stewards (mostly senior management) representing both departmental and enterprise-wide perspectives from across UNB. Data stewards are expected to: • Oversee the evolution of the data framework at UNB • Define procedures and data meanings • Implement policies for data in their areas • Assist in resolving cross-organizational data issues • Possess deep knowledge of their area and how data within the area is used • Get to know who is doing what with data across the university • Have a good grasp of the ‘big picture’, and can act to rationalize fixes for data issues. Data Management Working Group Data management requires the partnership of administrative, academic & technology expertise. Data management practice is a roadmap of tasks, artifacts, standards, guidelines, and best practices. It provides a structured framework for delivery of data-related projects. Those involved must collectively understand the information needs of UNB and its stakeholders, and maximize the effective use and value of data assets. Furthermore, the data management function must ensure efficiency in processing data assets, while maintaining privacy and confidentiality. Finally, unauthorized or inappropriate use of data and information must be prevented. The working group is responsible for actually implementing data policies and procedures across UNB. It is comprised of data managers who work with data on a regular basis. Business data managers are responsible for data content, context & associated business rules; IT data managers are responsible for the safe custody, transport, storage of the data and implementation of the business rules. Data managers, via the working group, are expected to: • Ensure that technical and business processes are in place to sustain data integrity which includes controls to safeguard data • Share expertise, tools and resources with units requiring assistance in managing the data • Participate in data quality issue resolution, in partnership with Data Stewards • Apply change management practices in maintenance of databases • See that data content and changes are auditable • Understand the data within their administrative authority, but be aware of other consumers and uses of that data across the enterprise

Terry Nikkel, AVP, ITS, March 9, 2016