Good analytics depends on a shared understanding of what the numbers mean. Google’s Developing Data Models with LookML introduces the modeling work that gives Looker users reusable definitions and organized ways to explore their data.
The actual course contains twenty-four videos, four quizzes and a resource document, with two required practical labs accessed separately. The free instruction moves from Looker and LookML foundations to model construction, derived tables and caching. It is intended to explain the developer-side modeling workflow rather than a general introduction to making charts.
Course at a glance
| Provider | |
|---|---|
| Platform | Google Skills |
| Level | Intermediate |
| Language | English |
| Estimated study time | 7 hours; provider full-course estimate including practical activities; instruction-only study time may differ. |
| Format | 24 videos, 4 quizzes, 1 reading/resource document; 2 separately accessed provider-required labs |
| Access | Advertised-free instruction; free learner account required. Labs, tools and product usage are separate. |
| Recognition | Provider recognition is subject to its activity requirements; no free badge or certificate promised. |
What you’ll learn
- Review Looker, LookML, the IDE and project version control.
- Explore dimensions, measures and modeling logic.
- Understand the course’s treatment of LookML dashboards and custom Explores.
- Review symmetric aggregation and filters within the model.
- Compare derived-table topics and learn the instructional role of caching and datagroups.
Skills you’ll gain
- Semantic-model vocabulary
- Dimension and measure design
- Explore planning
- Derived-table reasoning
- Model-governance discussion
Create a shared analytical language
The first lessons introduce Looker and LookML, the user interface, IDE, version control and how Looker writes SQL. That creates a foundation for the model-building sequence. The course then examines dimensions, measures and the logic that connects them, with examples of defining those elements in LookML.
The purpose of a reusable model is easy to see when several readers ask related questions of the same data. As an independent study exercise, describe a fictional metric in plain English before thinking about a model definition. Clarify what it represents and which question it is meant to answer. Use the plain-language definition to guide the questions you ask of a model.
The course’s dashboard and Explore topics connect those definitions with what business users can access. Its instruction does not guarantee that a model built by a learner will be correct, performant or suitable for an organization’s data without further review.
Understand the model’s supporting decisions
The later lessons cover SQL and native derived tables, persistent derived tables, caching and datagroups. These are part of the developer-side story: the model involves decisions about reusable query structure and how results are managed, beyond choosing a chart type.
Keep a record of the reasoning behind a definition or table when studying. An independent reviewer should be able to understand the analytical question, the intended interpretation and the assumptions being made. Those notes make a model easier to discuss with the people who will rely on its definitions.
The two reviewed labs cover dimensions and measures, and derived tables. They are provider-required practical activities for the wider course, but separate from the advertised-free instruction. Keep the practical requirements in mind if you plan to complete the wider course.
Free learning and practical access
Google advertises the instructional route as Free and requires a free learner account. The wider course has two required labs; those practical environments and independent Looker product access are separate and may involve costs. The seven-hour estimate describes the full course structure, not a measured lecture-only runtime.
Any provider badge depends on its required activities and access conditions. A free badge, professional certification or academic credit is not promised.
Explore more learning options in the free course catalogue.
Frequently asked questions
Is this the Looker analysis course or the modeling course?
It is the developer-side LookML modeling course. Its curriculum focuses on models, dimensions, measures, Explores, derived tables and caching rather than only end-user analysis.
Does the reviewed curriculum include version control?
Yes. The curriculum covers LookML project version control and includes a Git workflow example in Looker.
Will watching the instruction meet every completion requirement?
No such promise is made. The wider curriculum contains two required labs, separately accessed from the advertised-free videos, quizzes and resources.
Questions & discussion
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