When starting (or even considering) a data quality initiative, organizations need to know the major issues they are facing, in order to focus their efforts and quickly obtain the initial results.
To provide some background, an organization not only needs to know they have problems with contact addresses of their clients, they also need to know how many are missing or incorrect, including the cost/impact of this (e.g., undeliverable mail accounts for 15-20% of shipping costs incurred).
So what organizations really need to do is understand their data quality issues, in order to select the best approach to address them.
The objective of the Data Quality Assessment is to identify the data entities important to business, and the content and quality of these entities. Our Data Quality Assessment will provide you with an objective evaluation of the current state of your data assets—from identification of major data quality issues to quantification of business impacts and summary reports—and will also provide estimates of data quality improvement using an automated data quality tool.
In an effort to get the clearest possible picture, we would ask you to provide extracts of your data and conduct a few workshops to discuss your requirements, issues you are facing, and especially the business impacts of the issues. The Data Quality Assessment usually consists of the following steps:
- Business Analysis
- Workshops/interviews with business users
- Discuss data entities important to business, their issues and impacts
- Data Profiling
- Initial data analysis using DQC Profiling to discover data anomalies, typical defects, data structure, and dependencies
- Data Quality Assessment
- Attribute completeness and validity (formats and structure, reference etalons, typos, and abbreviation identification)
- Full address validation
- Duplicates identification
- Business rules validation
The deliverables include a detailed report with summary statistics and results interpretation, examples of identified data quality issues, and an evaluation of the results. As part of the DQ Assessment, we provide a tailored set of data quality management measures, ranging from technology-related (DQ Firewall, Automated Data Cleansing, Data Consolidation, Data Quality Monitoring and Reporting) to more process/business-oriented (data governance, Manual Data Quality Issues Handling, etc.).
Ataccama supports the solution
Ataccama provides both the technology (data profiling and data quality assessment functionality, predefined plans to identify & quantify the issues) and the DQM expertise (analytical skills to discuss the data quality issues and impacts, experience with the DQM design concepts, and the Data Quality Assessment methodology).
With our free DQ Analyzer you can execute the data profiling portion of the Assessment within minutes.
- Quick objective evaluation of data quality issues (data profiling)
- Subjective, business rule-based evaluation of data content
- Business-oriented identification of data quality issues, evaluation of impacts (fit-for-purpose)
- Basis for data quality management strategy/roadmap design
- Basis for continuous DQ Monitoring and Reporting and improvement
- Data discovery support (bulk data profiling)