With ever-growing data volumes it becomes a challenge to manage your data. This includes making sure that the data is fit-for-purpose and that it is of the right quality. This is, however, what your business depends on to provide the best customer experience,, to avoid risk and regulatory compliance issues and to best support your day-to-day operations. Data Quality Management will help you identify data quality issues and correct them.
DATA QUALITY
Data quality refers to the state of information. It can be measured according to 6 characteristics but on a higher level the definition of data quality is how well it is fit for the intended use. The better the data is fit for decision making, planning or operations, the higher the quality is considered. With the large number of data sources containing data nowadays, the consistency of data accross shared data assets is increasingly important. Solving data quality issues requires both good data governance and Data Quality Management.
Data Quality: start with good intent, manage with technology!
DATA QUALITY MANAGEMENT
Data Quality Management is about processes and technology that help deliver data to the organization in a way that meets the business requirements. Your business decisions are based on your data. The higher the quality of your data the better you can serve your customers, collaborate with your business partners and grow your business in a highly competitive market.
Implementing Data Quality in your organization requires a structured approach and starts with clear objectives, a DQ Framework with data quality policies and rules, and a proven approach (Plan, Do, Check and Act cycle).
