openIDL Navigation
Hicham Bourjali
Kevin Petruzielo
Brian Mills
Kelly Pratt
Lanaya Nelson
Joseph Nibert
Mike Nurse
Rambabu Adabala
Minutes:
First item: Moving in the direction of prepping for a discussion on 3/27 - Mason and Peter indexing their work
SQL tables have been made - for auto data standard - reference tables are needed. A request was made wrt business users being able to interact with codes - so JSON is now being used to co-generate SQL file.
Auto program wrt ingesting test amounts of data and produce a report - team is approaching this stage
Peter will rewrite extraction pattern to fit into new pattern
He will be adding documentation and formalizing openIDL auto data standard - then AAIS will load live data into node
Homeowners is next on the agenda.
Second item: Mason Waggoner
-Working through test data and table population, an issue arose wrt discrepancy in some of codes w/i the stat plan
-One instance concerned vehicle use codes - basic question: what do we do with codes that aren't directly coded w/i the stat plan. Question arose when looking at vehicle use - a code of 9 recurrently popped up - signaling drools not up to date with vehicle use. Should 9 be accepted? A drool rule could be missing.
-There may be an addendum if 9 is a valid value, otherwise the code 9 is incorrect.
-Conclusion of the group: likely an error (9) - backlog for drools may need to be created.
-9 may have gone through since it flew under the threshold
-Dale agreed to send a message to Susan and Reggie inquiring about special exceptions for vehicle use.
Looking ahead:
Mason will be working on homeowners and filling out that spreadsheet
A detailed plan will be ready the end of April
Peter has largely finished the decoding job. His goal is to rewrite the extraction pattern they had that worked against the old data standards - the pattern will be updated, sent to Tornquist after Jenny finishes the NAIC filing, and once Peter gets clearance - PA will document all of his work with personal auto and bring it back to this group
AAIS is providing a reference implementation for serverless data load relying heavily on AWS. Drools will be central to the validation. Using a react interface, lambdas and EFS - a parallel load and validate into a stage.
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