To perform a successful data conversion, you have to know a number of things. In this series, we have uncovered the following about our conversion: Scope of the conversion Infrastructure for the conversion Source of the conversion Target for the conversion Management for the conversion Testing and Quality Assurance for
Here on the Data Roundtable we've discussed many topics such as root-cause analysis, continual improvement and defect prevention. Every organization must focus on these disciplines to create long-term value from data quality improvement instead of some fleeting benefit. Nowhere is this more important than the need for an appropriate education strategy, both in
The bigness of your data is likely not its most important characteristic. In fact, it probably doesn’t even rank among the Top 3 most important data issues you have to deal with. Data quality, the integration of data silos, and handling and extracting value from unstructured data are still the most
