Data quality is an assessment of the fitness of the data to serve its intended purpose in a given context. The major aspects of data quality are- Accuracy, Completeness, Relevance, and Consistency, Update status, reliability, Representation ability and Accessibility. When these entire criterions are met then data is said to be of high quality for the organization and can be used for the intended purpose. Acceptable data quality is crucial for an organization for operational, transactional processes and the reliability of business analysis, business intelligence and reporting. Data quality is affected by the way data is entered in the organization, stored and managed. Therefore a proper data quality management is required to ensure the quality of data at all levels in the organization.
Why is data quality management necessary?
Data quality management is necessary and a very important part of the overall management process of the organization. This is the thing which a data oriented organization can never ignore it. The data related to the sales, customer leads and other processes is very important for the organization. When dealing with high amount of data, organizations have to be aware of the data quality at every level of the organization. Data can gather bad information and can face degradation in the quality while going through different stages of processes in the organization. This data has to be properly managed and maintained with a consistent or higher quality at every stage in the organization through a data quality management process.
An organizational database is also integrated to external sources of data which can include social networking platforms. The data coming from external sources have to be formatted and aligned with the standards of the organization where they are imported. In doing all these activities there is no surety that the data will be of the desired quality needed in the organization. Therefore a data quality assessment and management processes has to be applied at every step of the data management in the organization. It will apply data quality filters in the entry points and at other levels of the database management. Data validation and de-duplication activities have to be followed in order to improve the data quality.
The organizations who fail to manage the quality of the data will have to face countless number of issues at every level of the processes in the organization. Consider a bad data or duplicate data related to contact information in the customer database. If there is duplicity of the customer data then he may receive calls from your sales team many times and this may irritate your customer. If the customer information is wrong then your sales call may go to a wrong number or wrong email or may not go at all due to bad data. Therefore maintaining a data quality is required throughout the organization activities related to the data in the organization. With proper data management tools and activities it can be achieved.