October 26, 2026 · Vistelio
Most business users never open an Explore — they live in Sheets and Slides. This tutorial covers the two governed exits from your semantic layer into Google Workspace: Connected Sheets for Looker and Looker Reports (the Looker Studio-native reporting surface inside Looker), including the LookML, permissions, and performance work that makes them safe.
Read moreSeptember 21, 2026
Most runaway Looker queries are not a warehouse problem, they are a modeling problem. This tutorial shows how to use sql_always_where, always_filter, conditionally_filter, required_fields, and fill-in defaults to stop unbounded Explore queries before they reach your database.
Read moreSeptember 18, 2026 · Vistelio
Merged Results, cross-database joins, and modeled alternatives all promise to combine data from two Looker Explores or two warehouses. They behave very differently. This tutorial shows how each one actually executes, where the numbers go wrong, and a decision path for choosing between them.
Read moreSeptember 16, 2026
A practical guide to drill design in LookML: drill_fields on dimensions and measures, drill sets, controlling the drill overlay with link and html, Liquid-powered drill menus, drill_fields on explores and dashboards, and how to keep drills fast and permission-safe.
Read moreAugust 25, 2026
Explores in Looker are central to creating a powerful and flexible self-service analytics experience. They define the starting point for an analysis and enable users to dive into the data. Explores provide a way to define the scope of data to examine, and they establish the fields available for selection in a query. This article will dive into the concept of Explores in Looker, their structure, and how to create them.
Read moreAugust 25, 2026
One of the pillars of Looker's powerful capabilities is LookML, its proprietary data modeling language. This article will take a deep dive into LookML, focusing on the three key concepts: Views, Explores, and Models.
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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