I'm trying to develop a small reporting tool (with sqlite backend). I can best describe this tool as a transaction ledger. What I'm trying to do is keep track of transactions from weekly data extract:new (or add) - resource is new to my app since my app may not have tracked this resource before as it hasn't been seen via extracts.update (or hit) - there is a recent use of that resource, update retention period by another week.delete (or drop) - this item saw no use since last report (optional, but would be nice to have for graphing week-to-week changes in demand for resources).All I've got is a weekly data extract (pipe-delimited flat file) coming from a legacy archiving/record-management system that I have no control over.Each line can be distilled to basically this:resource_id | resource info | customer_id | customer_infoSample data:10| Title X       | 1 | Bob11| Another title | 1 | Bob10| Title X       | 2 | AliceThe goal is make it easy to report on resources that haven't seen use for X-months (based on last hit). There is a retention period where resources are kept around for ease of access if they're popular. A resource that hasn't seen use for 18 months is marked for long-term archival elsewhere. This must be a common problem. Wondering if there a general-purpose algorithm to determine what's new/same/removed between data sets (db vs. latest extract)?
Algorithm for determining transactions among weekly data series?
algorithms;data;transaction;text processing