analytics

Why did apparel drop? Ask with five named tools and a time window. No warehouse dump. No TikTok story. We are not publishing a 40% insight lift.

An associate asks "can we ship this SKU on this order?" and jumps five UIs. Six named read tools, evidence on every fact, row cap 25 — not a warehouse chatbot.

Finance asks why revenue dropped last week. Someone answers with a TikTok story and no tools. Hop table with evidence per step — Baymard 70.22% is industry context, not your diagnosis.

For an enterprise lake (~38 TB Iceberg, 8.4k small files), S3 Tables managed compaction cut Athena scan spend −35% — compaction OPEX −90% vs pre–July 2025 pricing on the same workload.

For a specialty retailer (~380 stores, 2.4M loyalty members), S3 Tables Iceberg silver plus Kinesis cart events cut dashboard refresh from 26 hours to 22 minutes — conversion reporting error dropped from 11% to 2%.

QuickSight isn't a Looker or Tableau replacement — but for analytics bolted onto the AWS data plane, it's the path that doesn't require a new vendor contract. Data sources, SPICE performance, embedded analytics, row-level security, and dashboards that survive scale.

S3 + Glue + Athena is the canonical AWS data-lake stack. It's also the one teams over-engineer the fastest. A reference architecture with the partitioning scheme, the Glue crawler config, and the Athena cost guardrails that keep query bills predictable as the lake grows.