Articles
Quality datasets are crucial for AI training, but the need to protect real-world data can slow development and implementation.
Data quality alone is no longer sufficient. Enter data observability, which is particularly suited to the shift to more decentralised data management.
AI and cloud are noteworthy trends in master data management, but ensuring there's a solid business case for MDM is the first priority.
Profiling source data early will provide useful insights into what the company will be dealing with from a source data structure and content perspective, says Bryn Davies, director at InfoBluePrint.
It is necessary to measure that which you are trying to improve, says Bryn Davies, MD of InfoBlueprint.
With a proper data management strategy, the entire business benefits from greater efficiencies, says Bryn Davies, MD of InfoBlueprint.
South African businesses are using business intelligence to drive data governance, says Bryn Davies, MD of InfoBlueprint.
In the building industry, things must be right the first time. The same ought to be true when it comes to business intelligence.
When assessing data quality, people tend to focus on the "data" part rather than on the "quality" part.
Organisations should re-examine how they model, store and present information
Data quality is about clean data - right? Wrong! That`s just a part of it, and, as data quality creeps to the centre of the radar screen, here are some important issues to consider.
Dirty data contributes to poor company performance, and in the worst of cases, complete failure.