Data validation is an activity verifying whether a combination of values is a member of a set of acceptable combinations based on certain rules, which express the acceptable combination of values. If the data satisfies the rules, it’s considered valid for the intended use. Data validation is crucial for further data processing, because a high-quality data set is the foundation for sound and convincing data analysis.
The purpose of data validation is to ensure the level of data quality. The quality of data has many aspects, accuracy, coherence and comparability, and the focus is on the structure of the data. Accuracy indicates the measurement of difference between the objective and the estimated parameter. Sampling and non-sampling errors could induce the difference. Sampling errors are not under the scope of data validation procedure, because they are not actually produced by errors in data. Non-sampling errors consist of errors of measurement, coverage, processing and non-response. General data validation mainly focuses on measurement errors. Identification of measurement errors usually lack in direct measure, so the evaluation is basically based on replicates on the same samples. Data coherence and comparability mean that statistics should be internally consistent, temporal and comparable among spatial areas.
We provide data validation services to handle raw data for our clients. We validate the data by adopting validation rules tailored for the projects of our clients' projects. Our data validation services will help our clients conduct their data analysis without concerns of poor quality of the data.Our Services
The first step of our data validation services is designing the process. We will design an appropriate plan to better meet the requirements of quality for data sets. There will be an overall study of data sets, factors, and their associations. Following that, a validation rule will be set for the data.
The validation process needs to be tested before the application. It will be implemented with a parameterization, thoroughly tested, tuned and finally become productive.
Data will be examined against the validation rules. A report of the results will be presented.
Reviewing, which includes feedback analysis and problem and error identification, is critical for further improvements of data validation process efficacy and data quality.
We also provide data validation service for tables, listings and figures to measure their readability, accuracy, coherence, and comparability.
We guarantee the confidentiality and sensitivity of our customers' data. We are committed to providing you timely and high-quality deliverables. At the same time, we guarantee cost-effective, complete and concise reports.
If you are unable to find the specific service you are looking for, please feel free to contact us.
References:
1. Van der Loo M. (2015) ‘A formal typology of data validation functions’, UNECE Work Session on Statistical Data Editing, Budapest.
2. Van der Loo M., Pannekoek J. (2014) ‘Towards generic analyses of data validation functions’, UNECE Work Session on Statistical Data Editing, Paris.
3. Essnet Validat Foundation (2016) Methodology for data validation 1.0.