Data Quality

Data Quality

Data quality is an assessment of data’s fitness to serve its purpose in a given context. Various aspects of data quality includes

• Accuracy
• Completeness
• Update status
• Relevance
• Consistency across data sources
• Reliability
• Appropriate presentation
• Accessibility

Acceptable data quality is crucial to operational and transactional processes. Data quality assurance (DQA) is the process of verifying the reliability and effectiveness of data. Maintaining data quality requires going through the data periodically and scrubbing it. Typically this involves updating it, standardizing it, and de-duplicating records to create a single view of the data, even if it is stored in multiple disparate systems. There are many vendor applications on the market to make this job easier.

e-Governance projects rely to a significant degree on existing data, existing systems and existing processes. Where these are already in a mess, ICTs adds more to it therefore existing and planned good governance reforms should reconstruct work systems and processes else, the project will fall into a garbage in, garbage out due to data quality problems.

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