Traditional systems development and implementation has focused on processes, rather than on data as the foundation of the enterprise. A data orientation represents a major cultural change. It is
not only a change in the way an organization delivers systems, it also implies a new way of perceiving, accessing and respecting the evolving asset of information by the business community.
The movement toward data orientation is akin to fighting a gravitational force; the opposition can be overwhelming, since many members of the IS community were not taught the fundamental importance
of data. Data is much more stable than process or organization. Success in developing a data orientation requires strong change agents and a set of carefully orchestrated plans. Sometimes,
developing a true data orientation requires a re-engineering of the IS and business organizations.
A Meta data strategy can assist in the achievement of the goals of data orientation by providing a focus for sharing the data assets of an organization. It offers recognition to the value of data
and its components and usage within and throughout the organization. A Meta data Strategy can provide a map for managing the expanding requirements for information that the business places upon the
IS environment. A Meta data Strategy highlights the importance of a central data administration department for organizations who are concerned about data quality, integrity and reuse. Finally,
development and implementation of a Meta data Strategy enables an organization to begin to measure the value of the information assets under their control.
Recently, many companies have embarked upon a strategic plan to redesign their entire systems environment. This plan should include the customization of a systems development and implementation
methodology, and should result in providing a data orientation for all facets of the organization. One way to ensure the success of this new orientation is to develop and implement a meta data
strategy. This strategy will advise the IS and business communities in how to view and use the data that a company captures and stores, turning data into information and knowledge.
Meta data is “data about data”. It is the collection of information about the data collected in an application or database. Examples of meta data include: definition of the data element, business
names of the element, systems abbreviations for that element, the data type (alphanumeric, decimal, etc…) and size of the element, source location, etc… All of these pieces of meta data are of
interest to various members of the organization’s community; some are of interest only to certain IS staff members, while other pieces would be very useful for business people attempting to
navigate through the corporate Data Warehouse.
The components of a Meta data Strategy would include:
Decide how meta data would be used in the organization
- Data Stewardship
- Data Ownership
Decide who would use what meta data and why
- Business definitions and names
- Systems definitions and names
- CASE models and element relationships
- Element sources and targets (programs, files, databases, etc…)
Determine training requirements
Identify sources of meta data (CASE tools, existing databases and files, paper documentation)
Determine the quality of the meta data sources (absolute, relative, historical, etc…)
Determine methods to consolidate meta data from multiple sources
Identify where meta data will be stored (central, distributed, both)
- Evaluate the meta data products and their capabilities (repository, CASE dictionary, warehouse manager)
Determine responsibility for:
- establishing standards and procedures
- maintaining and securing the meta data
- proper use, quality control and meta data update procedures
Establish meta data standards and procedures
- Naming standards (abbreviations, class words, code values, etc…)
- CASE modeling standards
- Meta data committee
Determine if the meta data storage will be active or passive
Determine the physical requirements of the meta data storage
Measure the use and effectiveness of the meta data
Implementing a corporate meta data strategy requires significant involvement from IS and business management, since resources from these areas will participate in the activities to put the
strategy’s concepts into place. Active executive support is also necessary to promote the benefits of organizing and controlling the meta data for the use of all interested parties, of changing
the culture to accept a new paradigm for managing the meta data assets. Without the active support of IS and business communities, and the proper use of meta data management tools such as a
corporate repository and modeling software, the success of creating and implementing a meta data strategy will be extremely limited.