Alan Paris

o Determining whether harmonized enterprise glossary and ontology are the keys to attaching meaning to data
o It’s not about defining terms, it’s about representing “meaning” consistently in a data context
o How do software tools in the marketplace help?
o Is linking data across the organization optional or a requirement?

The importance of establishing clear roles and specific accountabilities for data quality across the business, as well as, performance measures and incentives, is key to enhancing the process for applying data quality. During this session, panelists will address how to strike a balance between manual/sampling-based processes to measure and report on data accuracy vs. the use of automated tools to measure other aspects of quality.
o Realizing it takes more than having the right toolset to deliver but the process behind the quality
o Mitigating issues associated with applying data quality standards and encouraging people to act on them
o Producing metrics that show how to determine which quality your client data is or your product data
o Determining how to get the end system to adopt to the standards you want
o Externally looking at the client to be serviced and improving the flow of information from the point of onboarding
o Data quality and provenance from the perspective of a National Numbering Agency (NNA)

o Examining the cost of failureand compliance KYC within the organization

o Making a renewed emphasis onclient data, KYC and client onboarding

o Assessing the importance of KYCand the various processes around gathering evidences

o Preparing the reference datateam for being tasked with the responsibility for legal docs