As you start your next project, consider essential data governance planning, whether you have an official plan or program called Data Governance. As teams consider and plan IT projects that will enhance, upgrade, or extend existing Enterprise Applications, consider your organization’s data governance strategy, policies, and procedures to enable transforming your current data beyond the legacy Enterprise Data Warehouse (EDW) technology model to supporting modern data management applications that include analytical and machine learning models and other exponential technologies: AI, IoT, Business Process (BPA) and Robotic Process (RPA) Automation.
New enterprise system projects typically include modifying existing data models to support simplified user experiences, process automation, and external system integrations. These projects also include current to future state process mapping and modeling to enable visualizing, analyzing, and prioritizing business outcomes. Adding three (3) additional activities to your process mapping workshops allows you to align these extensions and enhancements into existing or new data governance initiatives that will directly support the speed of implementing these exponential technologies.
Business Objects
Capture Business Objects in the systems’ data model(s) such as Catalog Pricing Agreements, Repair Services Contracts, Item Catalog, Services Receipts, SiteX Work Orders, etc. Then align them to (1) types, such as master data, transactional data, or in-flight data; (2) integrated systems, such as EDW, ERP, Talent Management, etc.; and (3) primary or sub-process, for example, the data source in the system as a primary (Purchase Order) or sub-process (Purchase Order Dispatch to Vendor) for the enterprise Procurement process.
Data Owners & Stakeholders
Capture the organization’s ownership of the business object, such as the business unit, department, or operating unit, AND the entity’s stakeholders. These roles’ naming and definitions will vary for your organization, enterprise, or data governance plan/policy. The roles purposefully define the owner as the area or part that owns the data and is responsible for the data, including the actions for how and by whom the data is consumed within and outside the organization. Data Stakeholders are usually the primary users (maybe even the producer) of the data in that object. They are also typically consulted or informed if the data model is modified, published, and archived/deleted at the record or data model (attributes) level.
Gaps to Align Objects to Modern Data Management
Capture gaps for the business object in complying with existing or future data governance plans or policies. An example might be that the thing has been audited for records retention requirements but is not available in the data catalog outside of EDW documentation. This is not to develop a list of tasks for your project team but to understand where the object is in your enterprise’s data governance program. Your project teams’ understanding of these gaps will support design decisions on whether and how the data model can be modified during your current project or if the data model will be replaced in the near or long-term goals.
Data governance planning is increasingly important as your organization begins or continues its journey to the cloud. One of the most challenging parts is capturing and cataloging current enterprise data models that must be examined for inclusion and compliance with those plans. Your project team can quickly address these gaps while delivering current enterprise system projects and ensure that your system enhancements are ready for your organization’s “big data” initiatives.