Starting an enterprise data model without data governance is a hopeless task. Most companies understand the need for data governance but are often reluctant to install an additional layer of bureaucracy to achieve it. At a minimum, standards should apply to variable naming and also formatting standards for diagrams of logical or physical data models. By the same token, you also need standardized structure for abbreviations, acronyms and documentation requirements. This will make work easier and more efficient for existing employees, and it will dramatically lower the ramp up the effort for new employees and contractors.
Standards are a reflection of the collaboration between business and IT. Data governance activities should be led and executed by business people, and the end results used by data modelers, architects, and business analysts alike. How can you build a data model when you don’t understand the meaning of critical business data? Data governance is a perfect example of how business and IT strive for mutual goals: creating standards and guidelines to support the enterprise. In this presentation, we will discuss how to better align both skills to better serve the business strategy.