by Angela Guess
Gary Allemann of IT Web reports, “It is generally understood that quality information is an enabler for cost cutting, risk reduction and revenue enhancement. However, many companies have different approaches to managing their corporate information asset. These approaches range from ad hoc and tactical projects to meet specific goals, to strategic imperatives that seek to embed data quality principles across the corporate architecture. This makes it difficult to know where to start, what is effective, or whether the company is on track for success in meeting the data management challenge, and which of these myriad approaches is best.”
Allemann continues, “For many companies, data management remains a reactive process, with individual project teams or business areas identifying specific data issues that are impeding the ability of the project to achieve a specific goal. Short-term measures may include tactical data cleansing initiatives, with or without a tool, and typically do not take corporate standards and goals into account. This approach results in rework and unnecessary expense. The problems are never really solved, so data cleansing efforts tend to focus their limited resources on a few applications, in a never-ending cycle of rinse and repeat.”
He goes on, “Companies that recognise this waste are shifting to a new paradigm based on the principle that sustainable data quality improvement requires a more mature approach. This entails a metamorphosis from existing chaotic approaches to a more proactive approach that incorporates data quality metrics, standards, shared master data and data stewardship. An enterprise-driven focus on data quality management requires data management principles to be embedded in the corporate culture, and this needs to be driven both top-down and bottom-up.”
Read more here.
photo by:
epSos.de