Hotel source data is mutable in the past, so an append-only pipeline drifts away from the PMS without anyone noticing until month close. A practical guide to room-night grain, bitemporal modeling with Apache Iceberg, PMS ingestion, guest data scope, and file physics at hotel volumes.
Amazon Textract almost never fails loudly. A working guide to turning external PDFs and scans into structured data: picking the right operation per document family, parsing the block graph, routing on per-field confidence, and catching the limits that silently truncate your records.
Every task green, zero errors, and the dashboard still shows yesterday's numbers. Run status describes your code, not your data. Here is how to instrument freshness, latency and failure rate so your pipeline tells you before an analyst does.
Two portals, one house, two records. Merging them is easy. Merging the wrong two is invisible and expensive. A practical look at blocking, match scoring, survivorship rules and the time axis most listing pipelines get wrong.
Three CRM records, one person, and nothing in the logs to explain it. A practical walkthrough of what actually breaks when you unify Shopify, Stripe, CRM and support data: guest-checkout identity, duplicate and out-of-order webhooks, revenue that never ties to payouts, deletion requests that miss half your copies, and reverse ETL write loops. Organized by failure family, with schema and handler patterns you can apply directly.
A backfill that exits zero can still be missing a week of data, and nothing will tell you. This is a practical guide to the failure families behind silent gaps: pagination drift under a mutating source, retries that duplicate pages, prefix layouts designed for writes instead of reads, the seam where backfill meets live ingest, and the storage class rules that make mistakes expensive. Includes deterministic key derivation, S3 conditional writes, Athena partition projection, and a per-window manifest pattern that turns completeness into something you can query.
Most customer sentiment analysis pipelines run perfectly and still produce a number nobody should act on. Here are the failure families that cause it, from labels stamped on the wrong message to averages taken over a scale that was never numeric, plus a pipeline shape and a legal boundary worth knowing before you ship.
Textract rarely fails loudly. It returns a plausible result that is quietly incomplete: a truncated result set, a tick box read as an empty string, a clause split across a page break. A practitioner's guide to the failure modes that actually bite when you point Amazon Textract at contracts, technical reports and correspondence, plus how to choose between sync and async, which feature types are worth paying for, and where Textract stops being the right tool.
A GraphQL source can hand you a 200 OK, a populated data block, and a quietly broken column in the same response. Here is how to build a GraphQL data ingestion pipeline on AWS that catches partial errors, respects cost-based rate limits, resumes cleanly from a cursor, and notices when the schema moves under you.
AWS Glue zero-ETL replicates seven Zendesk entities, but only three of them ever remove a row. Here is how that gap quietly skews CSAT and knowledge base counts, plus the three IAM layers to wire, the two settings you cannot change after creation, and the CloudWatch metrics that make drift visible before someone spots it in a meeting.