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Smart DQ , also known as Intelligent DQ or Rule-Based DQ , without management and governance can compromise the underlying input data . “ One will always have various levels of data quality and a lot of people will focus on rule-based or Smart DQ but forget about the governance and management that ’ s needed ,” Tuppen explains .
On top of that , it ’ s necessary to control the data being used by the AI models .
“ Focusing on the integrity of the input data will mean that your insights from the applied AI will be much more trustworthy .”
As with architecture , Tuppen says that there is no single answer for how to store your data .
“ If you want a playground or a sandbox environment , where you can run generalised analytics against raw data ; that ’ s where you ’ d have , for instance , a data lake which may not have been modelled .”
Tuppen advises that if a business wants to slice , dice and drill down reporting capabilities , then they may typically need a relational database .
128 December 2023