A decade ago, data management solutions were a much different market than they are today. Instead of being a niche concept that was only used by a handful of businesses, it has now become a "must-have" solution and core system for many organizations. Not only is data management a critical part of decision making, it is also needed to push innovation and improve overall operations.
According to a recent article I read from Experian Data Quality, despite the growing importance of data, more companies are struggling to master management. A Dynamic Markets study reports that 94 percent of companies suffer from common data errors, and one of the main reasons for this is ineffective data management practices.
These organizations may have strategies in place, but they tend to be fragmented and become stagnant as poor habits form, such as only addressing issues from specific departments instead of seeing the big picture.
This is where data management best practices come into play. The article focuses on a three-pronged approach — detection, analysis and resolution. This strategy brings several benefits, which include:
- Cutting down on unnecessary expenditures by identifying relevant data faster
- Enhancing regulatory compliance
- Centralizing and consolidating data
- Establishing a benchmark that is weighed against key performance indicators.
Any company looking to improve its use of data needs to develop, prioritize and implement the right data management strategy aligned to the company's specific business needs and long-term goals.