Any discussion of Master Data Management automatically includes a discussion of Data Governance. The two go hand in hand. Successful MDM implementations require understanding data ownership, stewardship, and security, as well as determining business rules to be applied to the data. Specific business rules usually include rules for matching and consolidating data items as well as data quality checks. Read more
If your organization is seeking to better manage its information as a corporate asset that is to be valued and capitalized, you’re likely focused on implementing programs that will catalyze measurable business results from mountains of business information that may be the product of the last decade or more of digital transformation initiatives. Read more
Governance is the ongoing process of creating and managing processes, policies, and information. This includes strategies, processes, activities, skills, organizations, and technologies for the purpose of accelerating business outcomes. It also involves creating organizations, roles and responsibilities to perform this management. In our experience, many organizations address governance once and often without completing the necessary tasks. Organizations that excel in data and analytics governance continuously manage the process on an ongoing basis. Read more
IT and business leaders share a common goal – to leverage the data available to them in order to make more informed business decisions. The first step to achieving that goal is to create a data & analytics roadmap, a task many companies find daunting. Where do you begin?
“Most organizations are ineffective in communicating data & analytics-related concepts across departments, resulting in suboptimal management and utilization of information.”
– Doug Laney, Gartner Blog Network