September 21, 2026 · Vistelio
Retention grids usually escape the semantic layer and end up as one-off SQL. This tutorial models cohorts, period offsets, retention rate, rolling retention, and incomplete-period guardrails in LookML so analysts can slice them safely.
Read moreSeptember 14, 2026
BI Engine is the cheapest dashboard-latency win available to a Looker team on BigQuery, and most instances use it badly or not at all. This tutorial covers how BI Engine acceleration actually works, which Looker query patterns it accepts, how to size a reservation, how to prove hit rates from INFORMATION_SCHEMA and System Activity, and how to model LookML so your tiles stay in the accelerated path.
Read moreSeptember 10, 2026 · Vistelio
Most Looker tuning advice assumes BigQuery. This tutorial walks through what changes when your LookML model sits on Snowflake or Databricks SQL: connection settings, temp schemas for PDTs, warehouse sizing, query killing, and the dialect-specific LookML you should be writing.
Read moreSeptember 9, 2026 · Vistelio
A practical guide to Looker caching: datagroups, sql_trigger vs max_cache_age, persist_with on models and explores, datagroup_trigger for PDTs, ETL-driven cache invalidation through the API, and how to prove a caching policy is working.
Read moreAugust 25, 2026
Derived tables can be a powerful tool in a Looker developer's arsenal. They allow you to create tables on-the-fly from existing tables, essentially enabling you to perform ETL (extract, transform, load) operations directly within Looker. Looker's LookML provides two types of derived tables: non-persistent and persistent. In this post, we will focus on Persistent Derived Tables (PDTs), understand when to use them, and delve into the how.
Read moreAugust 25, 2026 · Vistelio
Define rollups inside explores with aggregate_table and let Looker route matching queries to them automatically. Covers the query-matching rules, designing a small set of rollups, datagroup and incremental refresh, and measuring the win in System Activity.
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