IN200M1_Part1_Katie Monroe

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Purdue Global University *

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200

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Information Systems

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Dec 6, 2023

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Data Governance Roles IN200M1 Part 1 Dr. Sheikh Shamsuddin By: Katie Monroe
A data governance structure is the collection of rules, processes, and role delegations that ensure privacy and compliance in an organization’s data management. Every organization has its own unique goals, needs, and structure. There are four layers to a data governance operating model; operational, tactical, strategic, and executive (Seiner, 2014, pg. 59). Each layer represents the decision levels for the data (Seiner, 2014, pg. 59). In this paper, we will discuss the first two layers; operational and tactical. At the operational layer, the data is business unit specific. In this layer, data stewards play a very important role in framing the data governance strategy. Data stewards are responsible for producing and using the data while creating definitions of data for their business unit (Schwab, 2022). They oversee the quality of any data created in their business function (Schwab, 2022). A data steward can have one or more relationships to data. They can be a definer of data, a producer of data, or a user of data. And depending on the relationship, the data steward has different levels of formal accountability with no authority over the data they define, produce, and use (Seiner, 2014, pg. 71). According to Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success by Robert Seiner, “anybody can be a data steward.” Most often, data stewards are those who work on the front lines and see opportunities where improved data quality would benefit certain groups. A sales representative may see value in having a report for data collected on sales for each quarter to evaluate which categories are needing more sales emphasis for the business. An accounting team member may see an error in the calculations in a specific expense account and need more data reported on the subject. It’s important to educate data stewards in their specific relationship to data. Definers should be accountable for defining data, producers should be accountable for data production, and users should be accountable for related to using data (Seiner, 2014, pg. 74). In this layer, you can also have data custodians. They
are typically apart of IT departments. Data custodians usually are divided into areas of expertise such as data modelling, database administration, and are responsible for maintaining, archiving, recovering, backing up data, and preventing data loss or corruption. Decisions made at the operational layer should only affect that level of the organization (Seiner, 2014, pg. 60). Looking at the tactical layer, this is where subject matter experts’ or data domain stewards’ initiates, facilitates, and mediates the resolution of cross-business area processes and data issues regarding their area of expertise. The primary responsibility of the data domain steward is to be accountable for how data in their domain are managed (Seiner, 2014, pg. 78). Domain data stewards are responsible for maintaining the referenced data and attributes for a business data entity. For example, customer data stewards manage the contract information, financial data, order history, or other relevant details for all customer records in a company (Roddewig, 2022). Domain data stewards often work across departments to track all relevant data. Some examples of specific domains could include customer data, product data, vendor data, finance data, sales data, or subsets of these domains or subject areas (Seiner, 2014, pg. 60). In this layer, it’s important to separate the data that crosses business units into subsets. There are 3 primary ways to separate domains of data. First is by subject area with the appropriate level of granularity to define the domains (Seiner, 2014, pg. 78). Second is by level-1 and level-2 data resources. Level 1 data resources as operational systems that address the needs of a single business unit (Seiner, 2014, pg. 78). Level 1 data can be managed locally or at the desktop. Level 2 is when data is fed from multiple level 1 data resources into master data management solutions or data warehouses where data are shared across business units (Seiner, 2014, pg. 79). The main issue in Level 2 data resources is data falling into numerous data domains adding complexity to the data governance program (Seiner, 2014, pg. 79). Lastly, separating data by organizational
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