Category: 04 Data Cleansing

Defines the mechanisms, rules, processes, and methods used to validate and correct data according to predefined business rules.

Data cleansing focuses on data correction to meet end user criteria as determined by data quality business rules addressing all applicable quality dimensions. Business rules provide a standard baseline for identifying data defects or anomalies which can a ect business operations. Data cleansing should be conducted at the data source or close to the original […]

1. A data cleansing strategy has been created and is consistently followed. 2. Standard data cleansing processes are established and sustained. 3. Data cleansing standards are consistently verified by all stakeholders.

1. Does the organization have a reusable set of data cleansing processes (automated and manual) to resolve data quality issues? 2. Is there a defined process for verifying corrections and assessing e ective- ness? 3. How does the organization cleanse duplicate records? 4. Are corrections implemented at the source of capture? 5. Are data cleansing […]

Data Requirements Definition contains more information related to development and management of requirements. Data Quality Assessment and Data Profiling provide information that can be leveraged to prioritize and guide data cleansing. Metadata Management provides guidance to ensure that necessary information is managed to support capture and logging of changes to data. Provider Management contains information […]

[tabby title=»Performed»] 1.1 Data cleansing requirements are defined and performed. Refer to Data Requirements Definition for more information related to devel- opment and management of requirements. Example Work Products Data cleansing requirements Data cleansing guidelines [tabby title=»Managed»] 2.1 Data cleansing activities adhere to data cleansing requirements, which are linked to process improvements to achieve business […]