Data management systems should monitor data performance in all three categories of data status: its collection, its processing and its management. A comprehensive system should assess and homogenize data as it’s collected, then detect when it may be corrupting or failing during processing. You can also use fully functioning programming to help configure a resolution. Last but not least, the system should also “learn” from its experiences and monitor future processing activities to avoid past errors. Ultimately, good data governance practices should achieve and maintain coherence and consistency across all the data assets used by the company. To do this, you can:
1. Begin with an assessment of all data types.
- Quality matters (see above); build quality assessment, management and monitoring into the overarching governance plan.
- Address all aspects of the information with your data consolidation considerations, including metadata and master data stores.
- Remember that data retention and security concerns are also primary, not just because they will protect your enterprise, but also because they will form the foundation for your regulatory and compliance mandates. Your system should monitor all data throughout all stages of the data life cycle.
- Don’t forget reporting properties. Your data is meaningless without proper reporting tools and standards to clarify its actionable relevance.
2. Assess data management systems. This process involves who uses the data, how and why.
- While virtually all corporate elements rely on data, most employees aren’t involved in its management. Clarify who in each department has a critical role in data usage and engage them in the assessment discussion.
- Another critical point is who has access to the data. Be sure to identify where walls and other safeguards around sensitive information should exist to prevent unnecessary disclosures.
- Users change over time, too, as workers join and leave the organization. Plan a monitoring system that triggers removals when employees leave your company.
3. Affirm your new system by adopting a ‘data governance policies and practices’ culture throughout your organization.
This overarching data governance process will develop as you develop your data management systems; recording it captures the whys, hows and whos of its significance to your enterprise. Plan to evaluate it annually, too; like everything else, data ages and needs constant monitoring and attention to retain its value.
Despite the passage of the years, data disasters continue to occur. By keeping a careful eye over both your corporate information and how it’s governed, you can ensure that your enterprise avoids suffering a data-driven failure. Further, maintaining best data management and governance practices will ensure that your organization is always optimizing its fundamental information and intelligence.
POST WRITTEN BY
Director, Digital Modernization | Principal Architect | Technology Evangelist for Sage IT Inc.