1) How is matching impacted by multiple survivorship groups:
2) Best practices for implementing new match rules when using Event
Streaming for integration
3) Rule vs. Relevance Based Match Rules
4) OV Values and Match Rules:
5) Matching advanced capabilities:
6) Match rule best practices for integrating new sources into production implementation
7) Match rule filtering by source system?
8) Recommendations around Transitive Matching
Scalability of match engine / no of rules – At Pfizer, we have 100+ countries loaded into Reltio and we are adding many new data sources as we load new markets. Even for the same sources each market has diff quality and profile of data
We always hear from Reltio PS team that we should try to limit no of match rules per tenant to around 20-25 max
Assuming it's not a hard limit but is this a real constraint which would cause performance issue. If we want to have generic rules for cross markets but then have specific rules for outlier markets etc. and want to increase to 50-100 rules for e.g. than is this an issue?
Is the constraint that the infrastructure is not set up to scale as needed for this?
For a large global company like ours, it seems unacceptable that we have an enterprise platform that doesn't scale for our business needs and data complexity making our match quality lower than it should be.
can we add source system name in filter option when defining the match rules?
is there a way to do an external matching via api based on rules defined ???
What tool are you using for transliteration? How can we reuse this tool?
Any plans to separate tokenization from individual match rules/groups and comparator classes?
Apart from traditional and relevance matching, can you speak a bit about bot (AI/ML) based matching, I remember Reltio team has been talking about it for a while
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