Data Cleansing Clause Samples
The Data Cleansing clause defines the process and responsibilities for identifying, correcting, or removing inaccurate, incomplete, or irrelevant data within a dataset. Typically, this clause outlines which party is responsible for performing data cleansing, the standards or methods to be used, and any timelines or reporting requirements. Its core practical function is to ensure that the data used or delivered under the agreement is accurate and reliable, thereby minimizing errors and improving the quality of outcomes based on that data.
Data Cleansing. 11.2.1 If the Solution Architecture requires that data cleansing is to be performed by the Service Provider, the Service Provider must process the Health Data and make modifications to the Health Data by:
(a) eliminating records that are clearly duplicates;
(b) correcting obvious misspellings and errors;
(c) ensuring that there are consistent descriptions, punctuation and syntax; and
(d) resolving any other obvious inaccuracy, omission or inconsistency issues, to meet the level of accuracy and consistency stated in the Solution Architecture.
Data Cleansing. The Contractor shall support the State, which is responsible for cleaning source data before phased migration conversions.
(1) The Contractor shall test and perform ETL processes, which generate anomaly reports when running ETL scripts. The Contractor shall provide these error reports to the State to assist its efforts in cleaning any legacy data that may require work. There are generally two dimensions of data cleansing:
(a) Compliance with required structural format; and
(b) Accuracy of the data. Testing and validating the structural format of data ensures that actual production data is structured in compliance with defined requirements for CIVLS. Data accuracy testing ensures that the data is accurate and up to date, typically through the State using sample random testing techniques.
(2) The Contractor shall use the then existing State suite of tools to identify anomalies in State legacy application source data that require cleaning. The State then can use this suite and other methods to clean the source data so it no longer presents anomalies for final conversion.
(3) When the source data is declared by the Project Administrator to be clean and ready for the State to convert, the Contractor shall perform a final test against the cleansed legacy data to ensure all issues have been resolved. Issues may be resolved by conversion business rules or direct intervention (e.g., replacement) of the data by authorized State employees. The Contractor shall either validate the data as being ready for conversion or identify additional anomalies for State resolution.