Several best practices in organizations today involve getting business users engaged in data quality initiatives because data governance is now a must-to-do thing in every organization. But many companies struggle to manage this critical process and many organizations use only a fraction of the organizational information to gain the actionable insight required to facilitate the better performance of the business. And they also fail to realize the cost associated with the inaccurate, inconsistent and bad quality data. The significant amount of revenue which is lost to bad data forces the organization to shift the data quality initiatives from occasional data cleansing methods to regular and ongoing quality data management plans.
This data governance is a continuous process of improving data quality which should be embraced at all the levels of the organization. Here are some of the best practices for quality data management which are already used by many successful companies all over the world.
Data Quality Assessment
You should start your data quality management process by doing complete analysis of the current state of your data. Complete data quality issues like information with errors, inconsistencies, missing fields and duplicity should be identified. The bad data is buried deep in the legacy systems and also received from external sources like third part systems, external applications or social networking platforms. The organizations should perform an independent analysis of the current data quality of the organization and provide a complete report about the statistics about the quality of data in the organization. According to current position of the data quality the new data governance policies should be developed to address the data quality management requirements.
Creating A Data Quality Firewall
Feeding bad quality data into the organization can not only cause issues in the processes of the company but can also damage good data. A virtual data quality firewall blocks any bad data at the entry point only and proactively stop the bad data from polluting the environment. A comprehensive quality data management solution should include the data quality firewall which will identify the corrupt data entering the system based on pre-defined rules.
Combine Quality Data Management Solutions With Business Intelligence
Business solutions allow organizations to find out which data solutions are more important to be utilized and need to be targeted for data quality management. These BI solutions help in collecting the data which needs to be analyzed and collected for cleansing and analysis for high quality.
Creating A Data Governance Board
Data governance boards are used for setting the data policies and standards and ensure that there is a central mechanism for resolving the data issues, facilitating and enforcing data quality improvement methods. It also helps in facilitating and enforcing data quality improvement techniques and taking proactive measures to stop any data related problems which can occur. The main objective of creative a data governance board is to mitigate the business risks which may arise from high quality data driven decision making processes and current business environment systems.