Data quality audit
Unfortunately, it is a reality that the quality of many information systems is unsatisfactory for various reasons, and often causes dissatisfaction among related parties.
The main reasons for commissioning data quality audit are assessing data accuracy, transition to new information systems, building data storage or the merging of organisations. Often an organisation needs audit results to assure the wider audience, owners or clients of data in the information system being accurate and checked.
High-grade information systems have to meet the needs and requirements of different parties. At the same time, one can say that the seriousness of the problem and the real cost of low-quality data is not always recognised. The real cost can include expensive data analysis, distorted reporting results, and under-usage of data due to uncertainty about the quality of data. Also, it might not be possible to identify the most profitable clients for a company.
Data quality audit provides organisations with several beneficial factors, including the following more important ones:
- Provides solutions to interesting business problems
- An opportunity to improve the entry checks of information systems
- An opportunity to systematically correct mistakes in a database
- Overview of insertion mistakes in databases and the non-conformity of data with business logic
- Provides information about the consistency, accuracy and timeliness of data, and enables to prevent the misuse of data, and reports on abuse
- Provides information about the reliability of analytical results, e.g. references to data which cannot be used in the current form for making decisions
- Improves the capacity of using data in different formats and from different databases
- If necessary, enables quicker merger and acquisition process
- We give recommendations on how to use the audit results for the benefit of an organisation.
Data quality evaluation process can be divided into 5 consecutive stages:
1) data quality audit
2) data quality rules and targets
3) data quality enhancement plans
4) deployment
5) data quality reports and tracking.
It is reasonable to commission data quality audit from external partners, because an auditor is experienced in test definition and results analysis, and can link emerged differences, their causes and effect on results. As a bystander, an auditor can ask questions somebody from the company itself has not yet thought of.
For data quality audit, Net Group uses software from SAS Institute, the world’s leading e-intelligence solutions company. SAS is the market leader in integrated data warehousing and decision support solutions.