Data Quality

Data quality is a perception or an assessment of data's fitness to serve its purpose in a given context.

Aspects of data quality include:

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

Within an organization, acceptable data quality is crucial to operational and transactional processes and to the reliability of business analytics (BA) / business intelligence (BI) reporting. Data quality is affected by the way data is entered, stored and managed. 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.

Mannara with its 17 yrs of expertise in BI has adopted a multi disciplinary approach to attack data related problems

  • Process Management - Ensure proper procedures before data load
  • Statistics – Focus on Analysis : Find and repair anomalies in data if any
  • Database – Focus on relationship : Ensure Consistency
  • Metadata / Domain expertise – Engage domain expertise to ensure correctness of meta data.

Want to know more?

Contact with our business consultant