Measuring the Pulse of Information Management and Governance · Data Governance
Anne Marie Smith, Ph.D. is a highly acclaimed data management professional, consultant, author and speaker in the fields of data stewardship and governance, data warehousing, data modeling, project management, IS strategic planning and metadata management. She holds a doctorate in Management Information Systems. Anne Marie has been a consultant in data management for organizations across many industries and she has taught in LaSalle University’s and Rowan University’s Management Information Systems departments. Anne Marie is on the faculty of Northcentral University. Anne Marie is a columnist for the EIM Insight journal and can be contacted at AMSmith823@yahoo.com
Many organizations have begun to explore the need for an enterprise data management strategy to leverage the value of the data and information they collect, store, use and propagate. In addition, executives have started…
Over the past five-ten years, most business leaders have seen that data is a critical asset, but they have struggled to implement effective management of this asset; valuation of it has been even more…
Less than one-quarter (25%) of small-medium businesses have heard about enterprise information management (EIM) and its components. Among those who have heard the term “enterprise information management”, over two-thirds said that they did not…
The Software Engineering Institute (SEI) developed a “Capability Maturity Model” (CMM), based on the work of Watts Humphrey at IBM. A maturity model strives to assist organizations in improving the quality of their software…
Traditional systems development and implementation has focused on processes, rather than on data as the foundation of the enterprise. A data orientation led by data governance represents a major cultural change. It is not…
Data quality is like the weather: many people talk about it but few address its challenges. Data governance can play an active role in the improvement of an organization’s data quality and develop a…
Many corporations are experiencing significant business benefits using data warehouse technology. Users report gains in market competitiveness (increased revenue) and information management (reduced costs). A data warehouse is a separate architecture used to maintain…
At some point during the initial phase of the data governance initiative, the team charged with designing the program will need to solicit and receive executive support. For many people this is a challenging…
Never before has the management of data been so important to organizations. Gartner estimates that about 25% of all development and enhancement efforts fail due to a lack of meta data or business requirement…
In reading many articles about the various data governance initiatives that have been started by organizations of all sizes and across all industries, one may sense that all such programs are immediately effective. Unfortunately…
As information management becomes more important to organizations, many are struggling with coordinating the components of EIM (meta data management, data governance, enterprise data management and architecture, data and information quality, data warehousing and…
Many enterprise information management (EIM) or data management projects don’t live up to their potential. EIM technology (data dictionaries, meta data management products, data modeling, data warehousing and business intelligence, data quality) have been…
The Merriam-Webster dictionary defines scope as “extent of treatment, range of activity or influence, range of operation." Once an organization has determined it needs a data governance program and the program’s existence has been…
Many organizations are examining the concepts of data governance and planning to implement a data governance program. Some organizations are concerned that a formal enterprise data governance program will take many months to implement…
A data strategy is a data management strategy – choices we make about how to manage data assets. These choices include: How we define data management, its scope, mission, long-term goals and short-term (12-24…
Readers of EIMInsight magazine (this publication), and others I have written for can tell that I am an avid reader; one of my favorite subjects is history. Over the years, I have read many…
Organizations considering a new approach to enterprise data management frequently wonder about the current state of their data management efforts. They don’t know where to start, what should be repaired, what should be left…
For many organizations, titles are one of the ways that performance is distinguished or acknowledged, while in other organizations there is no coherence in how different people’s activities are classified. In many efforts, a…
Data Governance is the practice of managing information to identify and improve its business value. Data governance provides a practical methodology for data with business priorities. Although meta data is not new, its importance…
Models are created not only to represent the business needs of an application but also to depict the business information needs of an entire organization. An enterprise model, which is comprised of one or…
Requirements gathering (data, meta data and process) are a vital part of successful project management and information management —well-known and publicly available research, such as the Standish Group’s Chaos Report, has shown this to…
Along with a deep understanding of the data and meta data, data stewards must thoroughly understand the business processes needed for optimum performance. An excellent way to gain this understanding is to carefully and…
As the United States (USA) selects a new president and chooses from candidates for other offices, many thoughts may turn to the role of politics in data governance. Politics is the process by which…
In a prior article, I attempted to outline the reasons for creating a vision for data governance within an organization. Since many strategic thinkers recommend developing a mission statement as well as a vision…
A recent book by a Yale University econometrician, Ian Ayers, looks at a new trend in organizations, changing the decision-making process from one based on expertise and intuition to a data-based effort. This change…
Governance is defined by Merriam-Webster as “the continuous exercise of authority over and the performance of functions for an organization”, so “data governance” would seem to mean the exercise of control over data. However…
Many organizations are pursuing numerous data-oriented initiatives, such as Customer Integration, master data management, data warehousing and business intelligence, etc. These efforts all require a thorough understanding of the data needed to answer business…
Most data governance initiatives start as a result of either an event (discovery of data security breaches, development of a data warehouse, reaction to a poor data quality audit, etc.) or as part of…
Many companies are discovering a problem when they attempt to integrate separate systems into an enterprise view of data – poor data quality. This discovery often leads to the development of a data governance…
At the highest level, data governance is concerned with the management of data – its availability, currency, usefulness, accuracy and relationships with other enterprise data. Governance of data is not an IT function, although…
Increasingly, enterprises are recognizing the value of a governance approach to the data found in their organizations. The potential benefits of data governance include rationalization of data for a common view of the business…
Generally, governance is a long-term strategic initiative, but data governance can also deliver short-term, tactical benefits. The need for both strategic and tactical approaches to data governance contributes to an organization’s confusion on where…
Governance defines the way we manage, monitor and measure different aspects of an organization. There are governance programs for managing information technology, governance programs for managing people and other tangible resources, and there is…
Data governance . What is it? Why is it important? What is the relationship between governance and stewardship? Does enterprise data management need data governance? These questions, and others, are asked and answered daily…
Generally, governance is a long-term strategic initiative, but data governance can also deliver short-term, tactical benefits. The need for both strategic and tactical approaches to data governance contributes to an organization’s confusion on where…
One of the main areas of responsibility for any data steward is the enforcement of data integrity. Most data administration texts define data integrity as “attention to the consistency, accuracy and correctness of data…
The classic definition of a Data Warehouse is architecture used to maintain critical historical data that has been extracted from operational data storage and transformed into formats accessible to the organization’s analytical community. The…
Since the introduction of the term “data warehousing” in 1990, companies have explored the ways they can capture, store and manipulate data for analysis and decision support. At the same time, many companies have…
Many corporations are experiencing significant business benefits using data warehouse technology. Users report gains in market competitiveness (increased revenue) and information management (reduced costs). A data warehouse is a separate architecture used to maintain…
The mission of a repository is to provide an efficient method for controlling the definition, access and use of metadata so this information can be used to provide meaning to corporate data. "Metadata" is…
Throughout the history of Information Resource Management, there have been questions surrounding the necessity for multiple disciplines within the IRM domain. Many organizations do not recognize the essential differences between Data Administration and Database…