Category Archives: Data Quality

3 new ideas improving datawarehouse lifecycle quality process

3 new ideas on improving the data warehouse lifecycle quality process

Data warehousing for business intelligence and “big data initiatives” continues to gain significance as organizations become more aware of the benefits of decision oriented data warehouses. However, a key issue, with the rapid development and implementation of data warehouses, is that data quality defects are

3 key data integrity testing strategies for DW/ BI

3 key data integrity testing strategies for DW/ BI systems

Data warehousing and business intelligence users assume, and need, trustworthy data.In the Gartner Group’s Online IT Glossary, data integrity and data integrity testing are defined as follows:Data Integrity: the quality of the data residing in data repositories and database objects. The measurement which users consider

how to identify reduce DW BI data quality risks

How to identify and reduce DW/ BI data quality risks

An introduction to DW/ BI data quality risk assessmentsData warehouse and business intelligence (DW/ BI) projects are showered with risks – from data quality in the warehouse to analytic values in BI reports. If not addressed properly, data quality risks can bring entire projects to

7 data quality management principles

7 principles of data quality management

The principles of data quality management are a set of fundamental beliefs, standards, rules and values that are accepted as true and can be used as a foundation for guiding an organization’s data quality management. They have been adapted from ISO 9000 principles of quality