Big Data is produced through email, social media, online orders, and even online video games. Data is generated not only by phones and point-of-sale devices, but also by surveillance systems, …
Data Quality – Policy and Metrics
Data Quality – Policy Data Quality efforts should be supported by and should support data governance policies. For example, governance policies can authorize periodic quality audits and mandate compliance to …
Data Quality Program – Readiness Assessment / Risk Assessment
Findings from a readiness assessment will help determine where to start and how quickly to proceed. Findings can also provide the basis for roadmapping program goals. If there is strong …
Data Quality – Incident Tracking System
The incident tracking system will collect performance data relating to issue resolution, work assignments, volume of issues, frequency of occurrence, as well as the time to respond, diagnose, plan a …
Data Quality – SLA – Service Level Agreements
A data quality Service Level Agreement (SLA) specifies an organization’s expectations for response and remediation for data quality issues in each system. Data quality inspections as scheduled in the SLA …
Data Quality Reporting
The work of assessing the quality of data and managing data issues will not benefit the organization unless the information is shared through reporting so that data consumers understand the …
Data Quality Assessment
DQ Analysts will need to sort out and prioritize findings. The goal of an initial Data Quality Assessment is to learn about the Data in order to define an Actionable …
Reference and Master Data Management – Guiding Principles
Shared Data: Reference and Master Data must be managed so that they are shareable across the organization. Ownership: Reference and Master Data belong to the organization, not to a particular …
Data Quality – Data Profiling
Data Profiling is a form of data analysis used to inspect data and assess quality. Data profiling uses statistical techniques to discover the true structure, content, and quality of a …
Data Quality – Causes of Data Quality Issues – Part-03
Issues Caused by System Design Failure to Enforce Referential Integrity: Referential integrity is necessary to ensure high quality data at an application or system level. If referential integrity is not …